Top 10 AI Engineer CV Examples

Fatima McKenzie
07700 90XXXX
fatima.mckenzie@example.com
fatimamckenzie
Leeds, West Yorkshire, LS6 2QH
SUMMARY
Early-career Junior AI Engineer with a BSc in Business Analytics and practical training in AI and data workflows. Apply Excel, SQL and Python to prepare datasets, check data quality and develop clear analysis, then present findings through Tableau and Microsoft Power BI dashboards. Evaluate introductory AI business scenarios in Microsoft lab exercises and document methods for non-technical reviewers. Build a project portfolio through instructor-led training, mentor feedback and hands-on practice, with preparation for Microsoft credentials and career interviews.
EDUCATION
Bachelor of Science in Business Analytics
2024
University of Bradford
Bradford, West Yorkshire
TECHNICAL SKILLS
Programming Languages: Python, SQL, R
Spreadsheets: Microsoft Excel, Google Sheets, LibreOffice Calc
Business Intelligence: Microsoft Power BI, Tableau, Looker Studio
Cloud Platforms: Microsoft Azure, AWS, Google Cloud Platform
AI Services: Azure AI Services, Azure Machine Learning, Microsoft Copilot Studio
Data Manipulation: pandas, NumPy, Polars
Data Visualisation Libraries: Matplotlib, Seaborn, Plotly
Relational Databases: Microsoft SQL Server, PostgreSQL, MySQL
Notebook Environments: Jupyter Notebook, Google Colab, Microsoft Fabric notebooks
Microsoft 365: Microsoft 365 Copilot, Microsoft SharePoint, Microsoft Teams
SKILLS
SQL query writing
Python data cleaning
Microsoft Power BI
Tableau dashboards
Excel
Data visualisation
Data quality checks
Dataset preparation
Dashboard development
Azure AI fundamentals
Copilot administration
AI use-case evaluation
Analytical documentation
Business communication
Portfolio development
EXPERIENCE
Junior AI Engineer Training Project
Mar 2026 - Oct 2026
Career Programme Lab
Remote, United Kingdom
Completed instructor-led online training and hands-on Microsoft lab exercises, applying Excel, SQL and Python to organise, clean and manipulate a retail dataset for a practical analysis portfolio.
Wrote and optimised SQL queries, checking joins, filters and output consistency before using Python data-quality checks to prepare dependable analysis-ready records.
Built Tableau and Microsoft Power BI dashboards to present sales and customer-service trends, documenting design choices so findings could be understood by non-technical reviewers.
Tested introductory Azure AI scenarios and Microsoft 365 Copilot and agent administration tasks in a controlled lab, recording business use cases and fundamental administration considerations.
Used mentor feedback, the career-coach CV masterclass, exam preparation and interview practice to refine the project portfolio and communicate technical decisions clearly.
Business Analytics Capstone Project
Jan 2024 - May 2024
University Project
Bradford, West Yorkshire
Analysed public transport service data in Excel and SQL, resolving inconsistent categories and checking summary results against the original records.
Produced a Tableau dashboard comparing service patterns across routes, then presented the methods and findings to course assessors in a concise project demonstration.
Data Analysis Course Project
Oct 2023 - Dec 2023
University Project
Bradford, West Yorkshire
Used Python to clean and manipulate a teaching dataset, documenting missing-value and validation decisions before producing a reproducible analysis.
Created a Microsoft Power BI report from the prepared data and explained how the visuals supported a sample business decision.
Evaluated introductory AI business scenarios and Azure AI concepts through coursework, distinguishing suitable use cases from questions requiring further review.
LEADERSHIP, AWARDS & RECOGNITION
Peer mentor, Business Analytics cohort, University of Bradford, 2023 to 2024: shared study resources and supported new students with introductory data coursework.
Course representative, Business Analytics cohort, 2023: gathered student feedback and presented recurring course questions to teaching staff.
Dean's List, University of Bradford, 2023.
Commended capstone presentation, Business Analytics programme, 2024.
CERTIFICATIONS
Microsoft Power BI Data Analyst (PL-300)
2026
Microsoft Azure AI Fundamentals (AI-901)
2026
Microsoft AI Business Professional (AB-730)
2026
Microsoft 365 Copilot & Agent Administration Fundamentals (AB-900)
2026
PROFESSIONAL AFFILIATIONS
Member, BCS, The Chartered Institute for IT, engaging with a professional community focused on computing and digital practice.
Member, Royal Statistical Society, engaging with a professional community focused on statistics and data analysis.

Isla Ahmed
07700 90XXXX
isla.ahmed@example.com
islaahmed
Coventry, West Midlands, CV3 4FJ
SUMMARY
Career-transition candidate developing AI engineering capability through applied machine learning and generative AI projects. Build Python prototypes for car price prediction, sentiment classification and a retrieval-augmented customer service chatbot, preparing data and evaluating model outputs to understand their strengths and limits. Use prompt engineering and a vector database to ground chatbot responses in a knowledge base, with attention to privacy, bias and fairness. Training in neural networks, large language models and object-oriented programming is supported by Microsoft AI-900 certification, AWS Cloud Practitioner study and project presentations.
EDUCATION
BSc Psychology
2020
Coventry University
Coventry, UK
AI Engineering and Machine Learning Training Programme
2026
Northstar Digital Academy
Online, self-paced
Coursework: AI engineering fundamentals, neural networks, large language models, data workflows, prompt engineering, retrieval-augmented generation, machine learning and AI ethics.
TECHNICAL SKILLS
Programming Languages: Python, SQL, JavaScript
Machine Learning Libraries: scikit-learn, XGBoost, LightGBM
Data Analysis Libraries: NumPy, Pandas, SciPy
Visualisation Tools: Matplotlib, Seaborn, Plotly
AI and NLP Libraries: Hugging Face Transformers, NLTK, spaCy
Notebook Environments: Jupyter Notebook, Google Colab, JupyterLab
Development Environments: Visual Studio Code, PyCharm, GitHub Codespaces
App and Web Frameworks: Streamlit, Flask, FastAPI
Vector Databases: Chroma, FAISS, Pinecone
Cloud Platforms: Amazon Web Services, Microsoft Azure, Google Cloud Platform
Version Control: Git, GitHub, GitLab
Data Formats: CSV, JSON, YAML
SKILLS
Python programming
Machine learning
Generative AI
Neural networks
Large language models
Object-oriented programming
Data preparation
Model evaluation
Prompt engineering
RAG
Vector databases
Knowledge bases
Sentiment analysis
Data visualisation
AI ethics
EXPERIENCE
Trainee AI Engineer, RAG Customer Service Chatbot
Jan 2026 - Oct 2026
Capstone Project
Remote
Created a customer service chatbot prototype that retrieved relevant answers from a curated knowledge base, using Python, prompt engineering and retrieval-augmented generation (RAG) to ground responses in source material.
Prepared and organised source documents for retrieval, then connected a vector database to support semantic search and context selection for incoming questions.
Tested representative customer enquiries against expected answers, recording retrieval gaps and refining prompts and source content to make responses more relevant and traceable.
Documented data privacy considerations and potential bias in the prototype, and presented its design choices and limitations during a virtual oral examination.
Trainee AI Engineer, Sentiment Analysis
Sep 2025 - Dec 2025
Academic Research
Remote
Built a sentiment analysis classifier with Hugging Face using a labelled text dataset, reviewing examples and preparing the data before model evaluation.
Compared classifier outputs with labelled examples to identify misclassifications and explain how dataset composition could affect fairness and model behaviour.
Presented the model workflow, evaluation findings and responsible-use considerations in a project report, applying AI ethics principles including bias and data privacy.
Trainee AI Engineer, Machine Learning and Streamlit
Jun 2025 - Aug 2025
University Project
Coventry, West Midlands
Developed a Streamlit car price prediction app in Python, turning a cleaned vehicle dataset into an interactive demonstration of a machine learning workflow.
Used Pandas and NumPy to inspect, clean and prepare records, then applied Matplotlib to visualise feature patterns before training and testing regression models with scikit-learn.
Compared machine learning algorithms using held-out test data and documented the evaluation approach, limitations and results for a course presentation.
Used Jupyter Notebooks and VS Code to practise Python fundamentals and object-oriented programming (OOP), keeping code and project notes organised for review.
LEADERSHIP, AWARDS & RECOGNITION
Received commendation in the training programme’s 2026 final project review for clear project documentation and discussion of responsible AI.
Organised an informal peer study group for Python and machine learning learners in 2025–2026, sharing revision notes and facilitating weekly practice discussions.
CERTIFICATIONS
Microsoft Certified: Azure AI Fundamentals (AI-900)
2026
AWS Certified Cloud Practitioner
2026
UK-accredited AI engineering programme qualification
2026
PROFESSIONAL AFFILIATIONS
Member, British Computer Society (BCS), engaging with a professional community focused on computing and technology.
Member, Association for Computing Machinery (ACM), participating in an organised community for computing professionals and learners.

Benjamin Ross
07700 90XXXX
benjamin.ross@example.com
benjaminross
Leeds, West Yorkshire, LS1 4DY
SUMMARY
AI Engineer with eight years of software engineering experience across financial services, machine learning and production AI. Build and deploy practical systems that turn complex data into dependable products, including production scale Generative AI services integrated with established platforms. Combine Python and C# development with Azure data and model engineering, and work with product, security and engineering colleagues to shape requirements, test solutions and resolve issues after release. Recent delivery includes LLM applications, chatbots and agents that support financial operations, with monitoring and release checks to assess performance and response quality.
EXPERIENCE
AI Engineer
Dec 2023 - Present
Cedarstone Bank
Leeds, West Yorkshire
Designed and released production-scale Generative AI services for financial operations, combining LLM APIs, LangChain and a vector database to ground responses in approved internal material; introduced evaluation and release checks before user rollout.
Built secure chatbot and agent workflows with FastAPI and, from 2025, Microsoft Agent Framework, integrating them with existing services and Azure Cosmos DB to support operational queries beyond a proof of concept.
Developed data and model workflows across Azure AI Foundry, Azure Fabric, Azure Data Factory and Azure Synapse Analytics, preparing governed datasets for AI features while keeping the deployment path maintainable.
Established service monitoring, test scenarios and incident diagnostics for AI systems, helping technology and business stakeholders investigate response quality, latency and integration faults after release.
Presented design options and technical risks to product, security and engineering colleagues, and coached two developers on ML Engineering practices and the testing of AI/ML solutions.
Machine Learning Engineer
Mar 2022 - Nov 2023
Harbourline Payments
Bristol
Took transaction-risk models from experimentation into production, using Python, Azure Machine Learning Studio and repeatable testing to support timely review of unusual payment activity.
Analysed large payment datasets and applied classification and anomaly-detection methods, documenting model behaviour so operations stakeholders could use the resulting insights in decision workflows.
Created data preparation and deployment pipelines with Azure Data Factory and Azure Synapse Analytics, improving traceability between source records, model inputs and scheduled releases.
Monitored model performance after deployment and investigated data-quality or service issues with platform engineers, refining validation and retraining procedures where evidence warranted changes.
Software Engineer
Jun 2020 - Feb 2022
Cairn Mutual
Cardiff
Delivered Python and C# services supporting policy and claims workflows, translating operational needs into tested components that connected with existing business systems.
Built data processing routines for sizeable policy datasets and worked with analysts to check data quality, identify useful patterns and make reporting more actionable.
Applied software engineering practices including code review, automated tests, version control and release documentation, reducing avoidable integration issues for the wider technology team.
Junior Software Engineer
Aug 2018 - May 2020
Redbridge Analytics
Nottingham
Developed Python tools and C# application features for financial reporting products, turning specifications into maintainable code under guidance from senior engineers.
Prepared and analysed client datasets using established validation checks, resolving inconsistencies with analysts before information reached downstream reporting models.
Added unit tests and troubleshooting notes to software releases, building a sound foundation in reliable delivery and cross-functional technical communication.
LEADERSHIP, AWARDS & RECOGNITION
Received a Cedarstone Bank engineering commendation in 2025 for clear technical guidance and dependable rollout support on an AI service.
Mentored two software engineers in model testing, API integration and production support practices.
EDUCATION
BSc Computer Science
2018
University of Nottingham
Nottingham
CERTIFICATIONS
Microsoft Certified: Azure AI Engineer Associate
2024
Microsoft Certified: Azure Data Scientist Associate
2022
TECHNICAL SKILLS
Programming Languages: Python, C#, SQL
Cloud Platforms: Microsoft Azure, Azure App Service, Azure Functions
Azure Data Services: Azure Data Factory, Azure Synapse Analytics, Azure Fabric
Azure AI Services: Azure AI Foundry, Azure Machine Learning Studio, Azure Cosmos DB
AI Frameworks: LangChain, Microsoft Agent Framework, scikit-learn
API Frameworks: FastAPI, Flask, ASP.NET Core
Language Model Tools: OpenAI API, Azure OpenAI Service, Hugging Face Transformers
Vector Databases: Azure AI Search, FAISS, Chroma
Data Processing: pandas, NumPy, Apache Spark
Testing Tools: pytest, NUnit, Postman
Version Control: Git, GitHub, Azure Repos
Build and Deployment: Docker, Azure DevOps, GitHub Actions
SKILLS
AI engineering
Generative AI
Software engineering
Machine learning
ML Engineering
Python
C#
Azure
LLM APIs
Chatbots and agents
FastAPI
LangChain
Vector databases
Data analysis
Model monitoring
PROFESSIONAL AFFILIATIONS
Member, BCS, The Chartered Institute for IT, engaging with professional development and technical communities.
Member, The Alan Turing Institute community, taking part in organised professional activity related to data science and artificial intelligence.
LANGUAGES
English (Native)
French (Intermediate)

Arjun Richardson
07700 90XXXX
arjun.richardson@example.com
arjunrichardson
Bristol, BS1 5AH
SUMMARY
Senior AI Engineer with 11 years of experience delivering cloud software, machine learning services and practical AI solutions for complex organisations. Develop AI assistants and Retrieval Augmented Generation solutions that assess technical documents against infrastructure standards, identifying missing details before review. Move proofs of concept towards secure, maintainable services through testing, model evaluation and integration with enterprise systems. Collaborate with Enterprise Architecture, product owners and cyber security, data, infrastructure and networking specialists to clarify requirements, manage risks and shape responsible delivery. Apply Azure AI Foundry, Azure Machine Learning and MLflow alongside established software engineering practices, including automated testing, CI/CD and production monitoring. Bring experience serving higher education and public sector teams, supported by a computer science degree and current Azure AI credentials.
EXPERIENCE
Senior AI Engineer
Apr 2022 - Present
Wrenfield Digital
Bristol, UK
Leads delivery of AI assistants and workflow proofs of concept for higher education and public sector clients, translating product owner priorities into scoped releases and measurable acceptance criteria.
Since 2024, developed a RAG assistant using Azure AI Foundry and Azure Machine Learning to review cloud infrastructure designs against an approved document set. Retrieval tests and structured evaluations helped users identify missing configuration details and completeness issues before design review.
Refined prompt engineering and model configuration through test cases covering relevance, consistency and unsupported responses; documented limitations and responsible AI controls for operational handover.
Integrated LLM and AI services with enterprise APIs and document workflows, agreeing access and data handling with cyber security, data, integrations, infrastructure and networking colleagues.
Packaged services with Docker and Kubernetes, and established version control, automated testing, code review, CI/CD, monitoring and deployment documentation to support repeatable releases.
Applied governance standards, security controls, guardrails and model risk management reviews to delivery decisions, balancing quality, cost, maintainability and implementation speed while raising risks early.
Worked with Enterprise Architecture and AI Product Owners to assess cloud designs, shape follow-on use cases and create reusable implementation guidance as initial solutions moved towards production.
Built an AI application testing suite for the infrastructure design assistant, using versioned retrieval cases and expected response checks to identify document gaps and unsupported answers before deployment.
Compared candidate models against accuracy, latency and usage cost criteria for a design review workflow, then configured the selected service and API deployment path to meet agreed operational requirements.
Automated document intake and completeness checks by connecting the assistant to enterprise APIs, cutting manual preparation time by 30% across the pilot review queue.
Machine Learning Engineer
Jan 2019 - Mar 2022
Brackenridge Analytics
Cardiff, UK
Delivered Azure Machine Learning services for public sector operational teams, converting agreed analytical requirements into tested models and integration-ready components.
Introduced MLflow tracking for experiments and model versions, pairing documented evaluation criteria with reviewable release records to improve reproducibility and support model risk assessments.
Containerised scoring services with Docker and supported Kubernetes deployments, coordinating network access, infrastructure requirements and API integration with platform specialists.
Added automated tests, CI/CD checks and production monitoring, enabling teams to identify data-quality issues and model drift before they affected downstream workflows.
Presented model limitations, security considerations and implementation options to technical stakeholders, helping distinguish viable production use cases from exploratory proofs of concept.
Software Engineer
Jul 2017 - Dec 2018
Fieldstone Cloud Services
Manchester, UK
Built cloud-hosted services and API integrations for enterprise clients, converting technical requirements into maintainable components aligned with infrastructure and networking standards.
Used Docker to standardise development and test environments, and supported Kubernetes-based deployment work with platform engineers as client container platforms matured.
Strengthened version control, code review and automated testing practices across delivery work, improving the consistency of releases and the quality of handover documentation.
Worked with security and data teams to resolve access, configuration and information-handling issues before deployment.
Junior Software Developer
Jun 2015 - Jun 2017
Lattice Systems
Exeter, UK
Developed and tested backend features for internal business applications, using version control and peer review to deliver changes safely within scheduled releases.
Connected application components to REST APIs and relational data sources, documenting interface behaviour so support teams could diagnose integration issues.
Created repeatable build and test scripts for development environments, giving the team clearer feedback on regressions and reducing manual checks during release preparation.
LEADERSHIP, AWARDS & RECOGNITION
Recognised by a client delivery team in 2025 for clear technical documentation and a smooth assistant pilot handover.
Mentored two junior developers at Wrenfield Digital on testing practices, code review and maintainable API design.
EDUCATION
BEng Computer Science
2014
University of Exeter
GPA: 3.6
Exeter, UK
CERTIFICATIONS
Microsoft Certified: Azure AI Engineer Associate
2025
Microsoft Certified: Azure Data Scientist Associate
2022
Responsible AI: Applying AI Principles, Microsoft Learn
2024
TECHNICAL SKILLS
AI and Machine Learning: Azure AI Foundry, Azure Machine Learning, MLflow
Cloud Platforms: Microsoft Azure, Azure Blob Storage, Azure Functions
Container Platforms: Docker, Kubernetes, Helm
Programming Languages: Python, C#, SQL
API Technologies: REST, OpenAPI, JSON
Data Stores: Azure SQL Database, PostgreSQL, Microsoft SQL Server
CI/CD Tools: Azure DevOps, GitHub Actions, Jenkins
Version Control: Git, GitHub, Azure Repos
Testing Tools: pytest, unittest, Postman
Monitoring Tools: Azure Monitor, Application Insights, Prometheus
AI Frameworks: scikit-learn, TensorFlow, PyTorch
SKILLS
AI application development
RAG solutions
AI assistants
Prompt engineering
Model evaluation
AI workflow automation
Cloud design
Enterprise integration
Responsible AI
Model risk management
Security controls
Data governance
Risk identification
Production delivery
Technical documentation
PROFESSIONAL AFFILIATIONS
Member, British Computer Society (BCS), connecting with a professional community focused on computing practice and continuing development.
Member, Association for Computing Machinery (ACM), engaging with a professional community covering computer science and software engineering.

Owen Wood
07700 90XXXX
owen.wood@example.com
owenwood
Sheffield, South Yorkshire, S10 3GX
SUMMARY
Senior AI Software Engineer with 11 years of commercial experience building business critical ERP and SaaS products. Deliver C#/.NET back-end and full stack features, including large language model capabilities shipped in live software. Shape prompts and context, evaluate structured outputs and apply production safeguards across Azure services and established systems. Partner with product managers and subject matter experts to turn trade requirements into maintainable software.
EXPERIENCE
Senior Software Engineer
May 2022 - Present
Meridian Wholesale Software
Sheffield, South Yorkshire
Delivered C#/.NET features for a live ERP and SaaS platform used by wholesale and distribution businesses, taking work from product discovery through release and support.
In 2024, introduced a large language model feature into an established product workflow, developing prompts, supplying relevant context and returning structured outputs for user review.
Established evaluation cases for the model-assisted workflow, testing output quality and failure scenarios before staged release; added sensible fallbacks so core business processes remained usable when AI services were unavailable.
Built supporting services across SQL Server and PostgreSQL, with production-grade error handling, logging and monitoring to help engineers diagnose issues in live customer environments.
Worked with product managers and subject matter experts to translate trade-specific requirements into clear technical designs, using prototypes to test assumptions before hardening selected approaches.
Used Azure services and existing delivery pipelines to release product changes safely; applied GitHub Copilot and, from 2025, Cursor to accelerate implementation while retaining code review and testing standards.
Software Engineer
Jan 2019 - Apr 2022
Redwood Business Systems
Leeds, West Yorkshire
Extended a long-lived order and inventory platform with C#/.NET services and modern JavaScript interfaces, releasing features used by customer support and commercial operations.
Added PostgreSQL-backed reporting alongside existing SQL Server functions, documenting data behaviour and validating changes against established application patterns.
Helped modernise selected application components through incremental refactoring and automated checks, reducing release risk without disrupting existing customer workflows.
Deployed application components to AWS and improved operational logging, giving the support team clearer diagnostic information when integrations or scheduled processes failed.
Software Developer
Jul 2017 - Dec 2018
Pennine Digital Works
Bradford, West Yorkshire
Built customer-facing functions for a multi-tenant business software product using C#/.NET and JavaScript, converting product specifications into tested, maintainable changes.
Improved SQL Server queries and data validation for order-processing screens, helping users resolve incomplete records before submission.
Added error handling and release notes to new integrations, making changes easier for support colleagues to troubleshoot and explain to customers.
Junior Software Developer
Jul 2015 - Jun 2017
Cedar Applications
Huddersfield, West Yorkshire
Implemented small C#/.NET enhancements for a business applications team, following existing code conventions and contributing reviewed changes to regular releases.
Created JavaScript interface updates and SQL Server queries for customer account and stock functions, checking behaviour with developers and business users.
Wrote test notes and technical documentation for new features, building a sound foundation in production support and structured software delivery.
LEADERSHIP, AWARDS & RECOGNITION
Peer mentor for graduate and junior developers at Meridian Wholesale Software, supporting code-review practice and product onboarding.
Recognised by the Redwood Business Systems product team in 2021 for clear cross-functional delivery during an order-management release.
EDUCATION
BSc (Hons) Computer Science
2015
University of Huddersfield
Huddersfield, West Yorkshire
CERTIFICATIONS
Microsoft Certified: Azure Developer Associate
2021
Microsoft Certified: Azure AI Engineer Associate
2025
TECHNICAL SKILLS
Programming Languages: C#, JavaScript, SQL
Microsoft Frameworks: .NET, ASP.NET Core, Entity Framework Core
Relational Databases: SQL Server, PostgreSQL, SQLite
Cloud Platforms: Microsoft Azure, AWS, Google Cloud Platform
Azure Services: Azure App Service, Azure Functions, Azure Monitor
AWS Services: Amazon EC2, Amazon S3, Amazon CloudWatch
Web Technologies: HTML5, CSS3, React
Testing Tools: xUnit, NUnit, Jest
Development Tools: Visual Studio, Visual Studio Code, Git
AI Development Tools: GitHub Copilot, Cursor, Azure AI Foundry
SKILLS
C#/.NET
AI software engineering
Full-stack development
Modern JavaScript
SQL Server
PostgreSQL
ERP and SaaS
Azure
AWS
Large language models
Prompt design
Context management
Structured outputs
AI evaluation
GitHub Copilot
PROFESSIONAL AFFILIATIONS
Member, British Computer Society, engaging with a professional community focused on computing practice and continuing development.
Member, .NET Foundation community, participating in an organised professional community for .NET developers.

Andrew Morris
07700 90XXXX
andrew.morris@example.com
andrewmorris
Leeds, West Yorkshire, LS6 2AB
SUMMARY
Early-career AI Data Engineer with a BSc in Business Information Systems and a practical portfolio in data preparation, analysis, visualisation and introductory AI. Use Excel, SQL and Python to prepare and query datasets, then present findings through Tableau and Microsoft Power BI dashboards. Completed instructor-led training and live Microsoft lab exercises, applying mentor feedback to portfolio development and project documentation. Hold four Microsoft credentials spanning data analysis, Azure AI, AI business applications and Copilot administration, and communicate findings and data limitations clearly to non-technical audiences.
EDUCATION
BSc Business Information Systems
2024
University of North Trent
Nottingham, Nottinghamshire
TECHNICAL SKILLS
Programming Languages: Python, SQL, DAX
Spreadsheets: Microsoft Excel, Power Query M, Excel formulas
Business Intelligence: Microsoft Power BI, Tableau, Tableau Prep
Microsoft Data Platforms: Microsoft Fabric, Azure Synapse Analytics, Azure Data Lake Storage
Azure AI: Azure AI Foundry, Azure Machine Learning, Azure AI Search
Microsoft 365: Microsoft 365 Copilot, Microsoft Excel, Microsoft SharePoint
Data Formats: CSV, JSON, XML
Relational Databases: Microsoft SQL Server, PostgreSQL, MySQL
Python Data Libraries: pandas, NumPy, Matplotlib
Development Tools: Visual Studio Code, Jupyter, Git
Data Connectivity: ODBC, JDBC, REST
SKILLS
SQL query writing
Python data cleaning
Data validation
Excel analysis
Data analytics
Dashboard development
Data visualisation
Portfolio development
AI use case review
Microsoft lab exercises
Query optimisation
Dataset manipulation
Report writing
Stakeholder communication
Interview preparation
EXPERIENCE
AI Data Engineer, Portfolio Project
May 2026 - Present
Applied AI Portfolio Project
Remote
Developed a small retail sales portfolio project, using Python to clean and manipulate inconsistent product and transaction datasets before loading prepared tables for analysis.
Wrote and optimised SQL queries to check joins, summarise sales by product and period, and investigate anomalies; documented query logic so results could be reproduced and reviewed.
Created complementary Tableau and Microsoft Power BI dashboards, selecting visualisations that helped users compare sales patterns and identify incomplete records.
Completed instructor-led online training and practical exercises in a Microsoft lab environment, using mentor feedback to refine project documentation and prepare the portfolio for interviews.
Applied learning from Microsoft Azure AI Fundamentals and Microsoft AI Business Professional modules to assess suitable introductory AI use cases, and reviewed Microsoft 365 Copilot concepts through the Microsoft 365 Copilot & Agent Administration Fundamentals module.
Data Analytics Capstone Project
Sep 2023 - Jun 2024
University of North Trent
Nottingham, Nottinghamshire
Built an analysis of a simulated public transport dataset as a final-year capstone, using Excel and SQL to reconcile records and investigate service patterns.
Produced a Tableau dashboard and a Microsoft Power BI report for a student review panel, explaining the differences between the two views and documenting assumptions behind each measure.
Presented findings and data limitations in a concise written report, translating technical observations into practical options for a non-technical audience.
Data Reporting Student Lab
Jan 2023 - Aug 2023
University of North Trent
Nottingham, Nottinghamshire
Prepared coursework datasets in Excel and Python, correcting inconsistent categories and missing values before analysis in supervised lab sessions.
Used SQL queries to filter and aggregate sample records, then checked outputs against source tables to catch errors before submitting assignments.
Practised fundamental data visualisation and written interpretation, incorporating tutor feedback to make charts clearer and conclusions appropriately qualified.
PORTFOLIO
Title: Retail Sales Data Analytics Portfolio
Link: Portfolio project, no URL supplied
Description: Python data preparation, SQL analysis and complementary Tableau and Microsoft Power BI dashboards using retail product and transaction data.
LEADERSHIP, AWARDS & RECOGNITION
Faculty commendation for a clear and well-documented capstone presentation, 2024.
Recipient of a university academic progress bursary, 2023.
Organised a peer study group for introductory SQL and Excel coursework at the University of North Trent, 2023-2024.
Volunteered at the university student project showcase, helping prepare presentations and respond to visitor questions, 2024.
CERTIFICATIONS
Power BI Data Analyst (PL-300)
2026
Azure AI Fundamentals (AI-901)
2026
AI Business Professional (AB-730)
2026
Microsoft 365 Copilot & Agent Administration Fundamentals (AB-900)
2026
PROFESSIONAL AFFILIATIONS
Student member, British Computer Society (BCS), engaging with professional computing resources and community activities.
Student member, Association for Computing Machinery (ACM), connecting with computing and data-focused professional resources.
LANGUAGES
English (Native)
Welsh (Beginner)

Abigail Hussain
Cybersecurity Professional
07700 90XXXX
abigailhussain
Leeds, West Yorkshire, LS6 2AB
abigail.hussain@example.com
STRENGTHS
Threat analysis
Map data flows, trust boundaries and abuse cases before release, helping teams address AI security risks early.
Red-team testing
Turn attack exercises into practical mitigations and repeatable regression tests that give engineering teams clear next steps.
Risk communication
Present technical findings in terms of exploitability and impact, helping stakeholders agree which issues need attention first.
Cross-team partnership
Work with data scientists, engineers, architects and risk colleagues to turn security requirements into usable controls.
Analytical problem-solving
Investigate vulnerabilities and configuration gaps systematically, connecting evidence to realistic remediation for service owners.
SUMMARY
Cybersecurity professional with 12+ years of experience across security operations, cloud security, DevSecOps and AI security engineering, including five years securing machine learning and Generative AI systems. Assess LLM and foundation model risks through threat modelling, vulnerability assessment and red-team testing, then translate findings on prompt injection, jailbreaks, data leakage and adversarial attacks into practical safeguards. Build security controls across model development, training, evaluation and deployment, integrating guardrails, monitoring and automated checks into cloud environments and CI/CD pipelines. Partner with data scientists, engineers, architects and risk teams to establish AI security standards and model-risk evidence, supporting secure and responsible enterprise adoption.
EXPERIENCE
AI Security Engineer
Meridian Vale Technologies
Sep 2023 - Present
Leeds, West Yorkshire
Established threat modelling and security assessment practices for enterprise LLM and foundation-model deployments, mapping data flows, trust boundaries and abuse cases before release.
Led AI red-team exercises against internal AI-enabled applications, testing prompt injection, jailbreaks, model manipulation, data leakage and adversarial attacks; converted findings into prioritised mitigations and repeatable regression tests.
Designed AI security guardrails and monitoring for model access, sensitive-data handling and unsafe outputs, enabling engineering teams to detect and respond to misuse during operation.
Integrated security testing into CI/CD pipelines and DevSecOps workflows, using Python automation to check model interfaces, dependencies and deployment configurations before promotion.
Partnered with data scientists, AI engineers, architects, governance and risk teams to define enterprise AI security standards, control requirements and model-risk review evidence.
Assessed cloud security and secure configuration management for AI services, covering development, training, evaluation and deployment environments; documented remediation paths for platform owners.
Tracked emerging AI threats through red-team findings and threat intelligence reviews, updating regression scenarios and guardrails to support responsible adoption across enterprise applications.
AI Security Engineer
Brightforge Systems
Jan 2020 - Aug 2023
Manchester, Greater Manchester
Secured machine-learning services used for customer operations by reviewing data pipelines, model development workflows and deployment architecture against established security practices.
Built automated checks for model artefacts, access permissions and cloud configuration, reducing avoidable exposure before releases and giving engineering teams actionable findings.
From late 2022, assessed early Generative AI and LLM application prototypes, modelling prompt injection and data leakage scenarios and adding validation and access-control safeguards.
Worked with model developers to improve security testing across training and evaluation datasets, documenting adversarial examples and model-risk considerations for governance reviews.
Presented assessment results to technical and non-technical stakeholders, helping teams rank vulnerabilities by exploitability, data sensitivity and operational impact.
DevSecOps Security Engineer
Kestrel Ridge Cloud Services
Jun 2018 - Dec 2019
Birmingham, West Midlands
Embedded security checks in CI/CD pipelines for cloud-hosted services, combining code, dependency and infrastructure reviews with clear release criteria.
Automated configuration reviews with Python and infrastructure scripts, identifying excessive permissions and inconsistent controls before production deployment.
Worked with software engineers and cloud architects to threat model application changes and resolve vulnerabilities without disrupting delivery schedules.
Produced concise risk reports and remediation guidance for service owners, strengthening communication between engineering, operations and security teams.
Cloud Security Analyst
Westmere Financial Technology
Apr 2016 - May 2018
Nottingham, Nottinghamshire
Reviewed cloud access, network boundaries and service configurations for financial data applications, documenting security gaps and tracking remediation with system owners.
Used scripting to reconcile configuration records with approved baselines, helping operations teams identify drift and maintain secure environments.
Supported vulnerability assessments and security testing for application releases, explaining technical findings in terms of data protection and service risk.
Cyber Security Analyst
Northfield Digital Services
Jul 2014 - Mar 2016
Sheffield, South Yorkshire
Analysed security alerts and vulnerability reports for business systems, validating findings and escalating material risks through established incident and change processes.
Maintained clear investigation records and collaborated with infrastructure teams to verify corrective actions, improving the quality of evidence available for risk reviews.
Prepared trend summaries from recurring findings, helping stakeholders prioritise practical security improvements across supported services.
SKILLS
AI/ML lifecycle security
Generative AI
Jailbreak testing
AI governance
Foundation model security
Stakeholder management
Vulnerability assessment
Prompt injection testing
AI security engineering
Threat modelling
Cloud security
AI red teaming
DevSecOps
LLM security
Model risk
LANGUAGES
English
Native
Urdu
Proficient
MY CAREER
12.3Years
AI Security Engineer at Meridian Vale Technologies (3.2 Years)
AI Security Engineer at Brightforge Systems (3.7 Years)
DevSecOps Security Engineer at Kestrel Ridge Cloud Services (1.6 Years)
Cloud Security Analyst at Westmere Financial Technology (2.2 Years)
Cyber Security Analyst at Northfield Digital Services (1.8 Years)
LEADERSHIP, AWARDS & RECOGNITION
Recognised by the Meridian Vale engineering group in 2025 for clear, actionable AI red-team reporting and cross-functional knowledge sharing.
Mentored two security analysts on threat modelling, vulnerability assessment and communicating remediation priorities to engineering stakeholders.
EDUCATION
BSc (Hons) Computer Networks and Security
Sheffield Hallam University
2013
Sheffield, UK
CERTIFICATIONS
Certified Information Systems Security Professional (CISSP)
2022
AWS Certified Security – Specialty
2021
Practical AI Security and Threat Modelling, SANS Institute
2024
TECHNICAL SKILLS
Programming and Scripting: Python, Bash, PowerShell
Cloud Platforms: Amazon Web Services, Microsoft Azure, Google Cloud Platform
Identity and Access: AWS IAM, Microsoft Entra ID, HashiCorp Vault
Infrastructure as Code: Terraform, AWS CloudFormation, Ansible
CI/CD Platforms: Jenkins, GitHub Actions, GitLab CI/CD
Source Control: Git, GitHub, GitLab
Container Technologies: Docker, Kubernetes, Amazon EKS
Security Scanning: Snyk, Trivy, Checkov
AI and Machine Learning: PyTorch, TensorFlow, Hugging Face Transformers
Data and Model Formats: Apache Parquet, MLflow, ONNX
Network Security: Wireshark, Nmap, Suricata
PROFESSIONAL AFFILIATIONS
Member, UK Cyber Security Council, contributing to professional development and discussion of security practice.
Member, BCS, The Chartered Institute for IT, engaging with the UK technology and information security community.

Toby Stewart
07700 90XXXX
toby.stewart@example.com
tobystewart
Bristol, BS1 4DJ
SUMMARY
AI Research Engineer with more than six years of experience developing machine learning systems, including LLMs, agentic AI and financial crime compliance. Develop models from evaluation through production, combining foundation model fine-tuning, prompt engineering and human feedback to improve AML workflows. Partner with engineering and product teams to assess model performance, guide feature delivery and apply computer vision to financial documents. Bring a research-led approach to practical model development, benchmarking and MLOps.
EXPERIENCE
AI Research Engineer
Jan 2024 - Present
Cedarstone Analytics
Bristol, UK
Developed LLM-based workflows for financial crime compliance, helping financial institution clients review complex transaction alerts and AML case material with traceable model outputs.
Fine-tuned foundation models for specialist compliance tasks and used prompt engineering to improve extraction of relevant entities and risk indicators from varied documents.
Designed agentic AI systems that combine retrieval, tool use and controlled hand-offs, then tested their behaviour against representative compliance scenarios.
Built benchmarks and evaluation pipelines covering factual accuracy, case completeness and consistency; used back-testing against historical cases to guide model changes before release.
Established continuous improvement loops that incorporated human feedback from compliance analysts into model iteration and evaluation.
Introduced MLOps practices for versioning datasets and models, monitoring deployed systems and documenting release decisions with engineering and product colleagues.
Prototyped a computer vision model to extract information from scanned identity and financial documents, assessing performance across document types before integration planning.
Optimised an alert-review workflow by profiling model latency and batching document extraction, reducing median case processing time from 11 minutes to 8 minutes.
Partnered with engineers to release an analyst review feature with traceable model outputs and approval controls, reducing manual evidence collation by 18% across a pilot.
Machine Learning Research Engineer
Sep 2022 - Dec 2023
North Quay Intelligence
Bath, UK
Built machine learning prototypes for document triage and operational risk analysis, translating product questions into testable model objectives with software engineers and product managers.
From 2023, evaluated LLMs for structured information extraction, comparing prompt designs and fine-tuning approaches on a reviewed sample of compliance documents.
Created a benchmark and back-testing process that surfaced failure patterns across document classes and gave product teams a consistent basis for model selection.
Improved a computer vision pipeline for scanned forms by refining image pre-processing and evaluating classification results against a labelled test set.
Packaged repeatable training and deployment workflows, adding experiment tracking and model monitoring to strengthen MLOps practice.
Built an evaluation set from analyst-reviewed compliance documents and added error labels by document class, helping product teams compare model changes before release.
Machine Learning Engineer
May 2021 - Aug 2022
Lattice Risk Labs
Cardiff, UK
Trained custom machine learning models to prioritise unusual transaction activity for analyst review, balancing detection quality with the need for explainable operational outcomes.
Developed image classification and document-processing experiments for financial records, documenting dataset limitations and evaluation results for engineering stakeholders.
Built reproducible data preparation and model evaluation workflows, using error analysis to distinguish model issues from inconsistent source data.
Worked with product colleagues to turn analyst feedback into revised model requirements and focused test cases.
Junior Machine Learning Engineer
Jun 2020 - Apr 2021
Harbourlight Data Services
Exeter, UK
Prepared transaction and customer data for supervised modelling, applying validation checks that reduced avoidable data errors in research datasets.
Compared baseline classification approaches for financial risk use cases and presented performance trade-offs to senior researchers.
Documented model experiments and supported repeatable evaluation, building a sound foundation in machine learning research and engineering practice.
LEADERSHIP, AWARDS & RECOGNITION
Recognised by the Cedarstone Analytics product group in 2025 for clear evaluation guidance during the launch of a compliance model feature.
Mentored two junior colleagues at North Quay Intelligence on experiment documentation and model evaluation practices.
EDUCATION
MSc Artificial Intelligence
2019
University of Nottingham
GPA: 3.8
Nottingham, UK
CERTIFICATIONS
Generative AI with Large Language Models, DeepLearning.AI and Coursera
2024
Machine Learning Engineering for Production (MLOps) Specialisation, DeepLearning.AI and Coursera
2023
TECHNICAL SKILLS
Programming Languages: Python, SQL, R
Machine Learning Frameworks: PyTorch, TensorFlow, scikit-learn
LLM Platforms: Hugging Face Transformers, OpenAI API, Anthropic API
Computer Vision Libraries: OpenCV, Pillow, torchvision
Data Processing: pandas, NumPy, Apache Spark
Experiment Tracking: MLflow, Weights & Biases, TensorBoard
Cloud Platforms: AWS, Microsoft Azure, Google Cloud
Data Storage: PostgreSQL, MongoDB, Amazon S3
Development Tools: Git, Docker, Kubernetes
API Technologies: FastAPI, Flask, REST
SKILLS
AI research
Machine learning
LLMs
Agentic AI
Prompt engineering
Model fine-tuning
Computer vision
Financial crime compliance
Anti-money laundering
Model evaluation
Benchmarking
Back-testing
MLOps
Human feedback loops
Product collaboration
PROFESSIONAL AFFILIATIONS
Member, The Alan Turing Institute community, engaging with its data science and artificial intelligence professional network.
Member, British Computer Society, participating in its professional computing community.

Toby Hussain
07700 90XXXX
toby.hussain@example.com
tobyhussain
Leeds, West Yorkshire LS7 2AB
SUMMARY
AI/ML Engineer with 11 years of experience delivering production machine learning for streaming, publishing and digital media. Build audience segmentation and content recommendation products, turning behavioural and commercial questions into practical solutions. Develop scalable pipelines for high-volume media data and manage model deployment and monitoring across cloud environments. Work with data scientists, data engineers, product teams and business stakeholders to shape requirements and evaluate results. Recent projects include assessing generative AI and large language models for content metadata enrichment, with quality checks and human review informing recommendations for production use.
EXPERIENCE
Senior Machine Learning Engineer
Aug 2022 - Present
BrightWave Streaming
Manchester, UK
Led development of audience segmentation and content recommendation models for a streaming catalogue, using Python, PyTorch and large-scale viewing and behavioural datasets to improve the relevance of discovery journeys.
Built scalable AWS data and machine learning pipelines combining customer, content and advertising signals, making refreshed features available to modelling and product teams on a reliable schedule.
Established MLOps workflows for model testing, deployment automation and monitoring, integrating CI/CD checks so production releases could be assessed consistently and issues identified promptly.
Partnered with data scientists, data engineers and product managers to turn audience engagement questions into model requirements, evaluation plans and measurable product experiments.
From 2024, evaluated generative AI and large language model prototypes for content metadata enrichment, applying quality checks and human review before recommending any production use.
Machine Learning Engineer
Jan 2020 - Jul 2022
SignalFrame Publishing
Bristol, UK
Developed Scikit-learn models for reader segmentation and article recommendations, joining subscription, content and behavioural datasets to support more relevant digital publishing experiences.
Implemented GCP-based data preparation and feature pipelines for high-volume content and customer records, documenting data quality checks for repeatable model development.
Introduced model validation and monitoring practices that gave editorial product teams clearer evidence of recommendation quality and changes in audience response.
Worked with commercial stakeholders and product teams to translate publishing objectives into technical specifications, model evaluation criteria and delivery plans.
Data Scientist
Jun 2017 - Dec 2019
Lantern Broadcast Group
Cardiff, UK
Analysed viewing and advertising datasets to identify audience patterns for broadcast and digital content teams, using Python and TensorFlow to develop and assess predictive models.
Produced reusable data preparation workflows and model evaluation reports, helping stakeholders compare audience segments and content performance using consistent measures.
Collaborated with data engineers and editorial product colleagues to refine data definitions and convert business questions into practical analytical solutions.
Junior Data Analyst
Sep 2015 - May 2017
PixelReach Digital Media
Nottingham, UK
Prepared customer, advertising and behavioural datasets for digital content analysis, using Python and SQL checks to resolve inconsistencies before reporting and modelling.
Built early Scikit-learn classification models under senior review, documenting assumptions and evaluation results for campaign and audience insight teams.
Presented clear findings to account and product colleagues, translating analysis into testable recommendations for digital engagement activity.
LEADERSHIP, AWARDS & RECOGNITION
Recognised by the BrightWave Streaming product group in 2025 for clear model evaluation guidance during a content discovery release.
Mentored two early-career analysts in Python, model validation and communicating findings to non-technical stakeholders.
EDUCATION
BSc Computer Science
2013
University of Sheffield
Sheffield, UK
CERTIFICATIONS
AWS Certified Machine Learning – Specialty
2024
Google Cloud Professional Machine Learning Engineer
2025
Microsoft Learn: Azure Machine Learning fundamentals
2023
TECHNICAL SKILLS
Programming Languages: Python, SQL, R
Machine Learning Frameworks: TensorFlow, PyTorch, Scikit-learn
Cloud Platforms: AWS, Microsoft Azure, Google Cloud Platform
Data Processing: Apache Spark, Apache Beam, pandas
Data Orchestration: Apache Airflow, AWS Step Functions, Google Cloud Composer
Data Storage: Amazon S3, Google Cloud Storage, Azure Blob Storage
Databases: PostgreSQL, MySQL, BigQuery
Model Tracking: MLflow, Weights & Biases, TensorBoard
Containers: Docker, Kubernetes, Amazon ECS
CI/CD Platforms: Jenkins, GitHub Actions, GitLab CI/CD
Monitoring Tools: Prometheus, Grafana, Amazon CloudWatch
SKILLS
Machine learning
Python
TensorFlow
PyTorch
Scikit-learn
AWS
Azure
GCP
MLOps
CI/CD
Model monitoring
Audience segmentation
Content recommendations
Generative AI
Stakeholder engagement
PROFESSIONAL AFFILIATIONS
Member, British Computer Society, engaging with the UK computing profession and its machine learning community.
Member, Association for Computing Machinery, participating in its professional community for computing and artificial intelligence.
LANGUAGES
English (Native)
French (Beginner)

Sienna Marshall
07700 90XXXX
sienna.marshall@example.com
siennamarshall
Bristol, BS1 4DJ
SUMMARY
Early-career AI Engineer candidate and recent BSc graduate with practical training in data analysis, AI fundamentals and business-facing analytics. Apply Excel, SQL and Python to prepare and validate datasets, then present findings through Tableau and Microsoft Power BI dashboards. Complete portfolio projects that connect optimised queries and documented data-cleaning workflows with realistic business questions. Develop clear project explanations through instructor-led learning, Microsoft lab exercises and mentor feedback, with preparation for four Microsoft certification exams and entry-level interviews.
EDUCATION
BSc Information Systems
2024
University of the West of England
Bristol
TECHNICAL SKILLS
Programming Languages: Python, SQL, DAX
Data Analysis Software: Microsoft Excel, Microsoft Power Query, pandas
Business Intelligence: Microsoft Power BI, Tableau, Tableau Public
Microsoft Cloud: Microsoft Azure, Azure Machine Learning, Azure AI Studio
Microsoft 365: Microsoft Excel, Microsoft Teams, Microsoft SharePoint
AI Platforms: Azure OpenAI Service, Microsoft Copilot Studio, Microsoft Azure AI services
Data Visualisation: Matplotlib, Seaborn, Plotly
Databases: Microsoft SQL Server, Azure SQL Database, SQLite
Data Interchange: CSV, JSON, XML
Development Tools: Jupyter Notebook, Visual Studio Code, Git
SKILLS
SQL query writing
Python data cleaning
Microsoft Power BI
Tableau
Excel
Data analysis
Dashboard development
Data validation
Azure AI fundamentals
AI business analysis
Copilot administration
Technical documentation
Data visualisation
Interview preparation
Presentation skills
EXPERIENCE
Junior AI Engineer, Data Analytics Capstone
Jan 2026 - Present
University Project
Bristol, United Kingdom
Built a retail demand analysis portfolio project, using Excel to inspect source files and Python with pandas to clean, validate and reshape a 24,000-row dataset for consistent reporting.
Wrote and optimised SQL queries to join product, sales and stock tables, documenting assumptions and checking totals against source records before analysis.
Presented trends in Tableau and Microsoft Power BI dashboards, selecting clear filters and visualisations so a student review panel could compare product categories and seasonal patterns.
Used an instructor-led project brief and mentor feedback to refine the data workflow, explain limitations and prepare a concise project walkthrough for interview practice.
AI Fundamentals and Copilot Administration Lab
May 2025 - Dec 2025
University Project
Bristol, United Kingdom
Completed guided exercises in a hands-on Microsoft lab environment, applying Microsoft Azure AI Fundamentals concepts to assess sample AI scenarios, data inputs and appropriate human review.
Practised Microsoft 365 Copilot & Agent Administration Fundamentals through a simulated configuration exercise, documenting access considerations and a basic checklist for reviewing agent settings.
Applied Microsoft AI Business Professional course concepts to a case study, mapping a business question to an AI-supported workflow and presenting risks, expected value and practical adoption considerations.
Kept a learning log and revised explanations after mentor feedback, strengthening technical communication for certification exams and entry-level interviews.
Student Data Visualisation Project
Sep 2023 - May 2024
University Project
Bristol, United Kingdom
Analysed a small public transport dataset in Excel and SQL for a university assignment, checking missing values and inconsistent categories before producing summary tables.
Created a Tableau dashboard with documented filters and chart choices, then presented the findings to classmates and incorporated feedback into the final portfolio submission.
Used Python fundamentals to automate repeatable cleaning steps and compared the resulting records with the original data to verify accuracy.
LEADERSHIP, AWARDS & RECOGNITION
Received a faculty commendation in 2024 for a clear, well-documented data visualisation project.
Organised a peer study group for introductory SQL and Python coursework from 2023 to 2024, helping classmates practise core techniques.
Volunteered as a peer mentor at a university study-skills drop-in in 2023, supporting new students with project planning and presentation practice.
CERTIFICATIONS
Microsoft Power BI Data Analyst (PL-300)
2026
Microsoft Azure AI Fundamentals (AI-901)
2026
Microsoft AI Business Professional (AB-730)
2026
Microsoft 365 Copilot & Agent Administration Fundamentals (AB-900)
2026
PROFESSIONAL AFFILIATIONS
Student member, British Computer Society (BCS), engaging with a professional community focused on computing and digital careers.
Student member, Association for Computing Machinery (ACM), connecting with an international computing community and its learning resources.