US English



7 AI Engineer - Generative AI CV Templates with Example

By Ria · Last Updated On 23 October 2026
CV example — page 1

This practical guide shows you how to create an AI Engineer - Generative AI CV that makes your skills and results clear. You will learn how to organise relevant evidence and choose a professional layout for easy review.

Effective CVs for this role show how you design, test and deploy production-scale Generative AI solutions. Use clear examples of work with LLM APIs, chatbots or agents, Azure services and existing systems, alongside evidence of monitoring and issue resolution.

Compare the example in 7 layouts through PNG image previews, then open a version in the editor to customise it. The guide also covers ATS readability, useful CV sections and ways to present technical skills, projects, certifications and measurable results.

What Makes a Great AI Engineer - Generative AI CV in 2026

A strong CV makes production AI work easy to scan. Use focused experience bullets to show how you designed, tested and supported solutions after release.

Include relevant terms such as Generative AI, Python, C#, Azure, LLM APIs, FastAPI and model monitoring where they match your evidence. Add figures only when you can support them.

Note: CV examples are for educational purposes only. Use only information that accurately reflects your experience and qualifications. References to real organisations do not imply affiliation or endorsement.

#1 Simple One Column Format CV Example

The Simple One Column Format keeps all CV sections in one vertical reading path, a practical choice for straightforward review.

 
CV example — page 1   CV example — page 2

Why This Format Works

  • One reading path lets reviewers follow experience, then locate skills and credentials.
  • Longer achievement bullets can be read without moving between adjacent columns.
  • Education and certifications stay in the same flow as the rest of the CV.

Best For

  • Single-column reading
  • Sequential career histories
  • Detailed experience bullets
  • Text-led CVs
  • Straightforward section review

CV Keywords

  • 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.
  • software engineering
  • Python
  • Developed data and model workflows across Azure AI Foundry, Azure Fabric, Azure Data Factory and Azure Synapse Analytics
  • Cosmos
  • Presented design options and technical risks to product, security and engineering colleagues
  • work with product, security and engineering colleagues to shape requirements, test solutions and resolve issues after release.
  • Generative AI
  • Designed and released production-scale Generative AI services
  • machine learning
  • integrating them with existing services and Azure Cosmos DB
  • Data analysis
  • Monitored model performance after deployment
  • 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.
  • technical guidance
See all keywords
 

#2 Simple Two Column Format CV Example

The Simple Two Column Format places CV content in two reading areas, helping reviewers compare related sections while keeping the structure clear.

 
CV example — page 1   CV example — page 2

Why This Format Works

  • Distinct columns can group experience, skills and credentials without merging their section hierarchy.
  • Reviewers can compare career progression with supporting skills in a single glance.
  • Education and certifications have a clear place within the overall two-column structure.

Best For

  • Two-column content grouping
  • Several distinct CV sections
  • Side-by-side section review
  • Compact skills and experience
  • Quick movement between content areas

#3 Plain One Column with Shaded Labels CV Example

Plain One Column with Shaded Labels keeps the CV in a single reading sequence, useful when a direct route through sections matters.

 
CV example — page 1   CV example — page 2

Why This Format Works

  • A single vertical sequence lets reviewers follow experience sections in their displayed order.
  • Without parallel columns, technical skills and education remain on one reading route.
  • Section-by-section progression suits detailed career histories with several roles.

Best For

  • One-column section sequence
  • Sequential experience review
  • Detailed work histories
  • Text-focused applications
  • CVs with distinct content categories
 

#4 One Column Format with Photo Right CV Example

One Column Format with Photo Right pairs a single text column with a portrait at the right, keeping the text route clear while giving the photo a defined place.

 
CV example — page 1   CV example — page 2

Why This Format Works

  • A single text column gives reviewers a direct route through experience and career progression.
  • The continuous text area keeps achievement bullets together for a focused review.
  • Skills, education and certifications follow the same clear reading path.

Best For

  • Right-side portrait placement
  • Single-column CV reading
  • Detailed experience bullets
  • Sequential career histories
  • Section-by-section review
 

#5 Clean Two Column Sidebar Format CV Example

Clean Two Column Sidebar Format arranges CV content in two columns, offering a compact way to organise sections for scanning.

 
CV example — page 1   CV example — page 2

Why This Format Works

  • Two content areas help reviewers distinguish work history from supporting skills and credentials.
  • The paired columns give career experience and education separate visual space.
  • Reviewers can return to key sections without following one long vertical sequence.

Best For

  • Two-column section grouping
  • Compact content organisation
  • CVs with several information types
  • Separate experience and supporting details
  • Quick section navigation
 
 

#6 Two Column Format CV Example

Two Column Format sets CV content in two columns, suiting readers who want distinct information areas within one document.

 
CV example — page 1   CV example — page 2

Why This Format Works

  • Two columns let reviewers move between career history and skills without losing their place.
  • Separate content areas help keep education and credentials distinct from experience.
  • The layout supports a clear reading order across several CV sections.

Best For

  • Two-column reading
  • Parallel content areas
  • CVs with varied section types
  • Distinct education and experience sections
  • Organised document scanning
 

#7 Photo Header Two Column Format CV Example

Photo Header Two Column Format combines a portrait in the header with two body columns, useful when photo presentation and grouped content both matter.

 
CV example — page 1   CV example — page 2

Why This Format Works

  • Two body columns give reviewers separate areas for experience and supporting CV sections.
  • The header portrait has a defined place above the main content.
  • Grouped sections help reviewers move between career history, skills and education.

Best For

  • Portrait-inclusive CV presentation
  • Two-column content structure
  • Several distinct section groups
  • Grouped career information
  • Side-by-side content review
 
 
 

Why Build Your AI Engineer - Generative AI CV with ResumeInMinutes

ResumeInMinutes helps you organise your AI engineering skills, experience and education in a clear CV. Compare PNG image previews, then open an example in the editor to customise its content and layout.

  • Professional CV layouts
  • Clear, readable section structure
  • Space for relevant technical keywords
  • Organised skills and experience
  • PNG image previews
  • CV customisation in the editor

Choose a format that makes your technical evidence easy to follow. Give clear space to production delivery, AI tools, testing, monitoring and results.

 

See Also

 

Frequently Asked Questions

Are these AI Engineer - Generative AI CV templates ATS-friendly?

The examples use clear headings and sections that support scanning. Add relevant terms naturally, such as Generative AI, Azure, Python, C#, LLM APIs, LangChain and model monitoring, when they match your experience.

Are these separate CV examples or different layouts of one example?

This page shows one role-focused CV example in different layouts. Compare the PNG image previews, then open an example in the editor to customise it.

What should an AI Engineer - Generative AI CV include?

Include a focused summary, relevant experience, skills and education. Show how you have designed, tested or deployed AI solutions, integrated them with existing systems, and monitored performance or resolved issues.

Which CV layout works well for this role?

Choose a layout with clear headings and an easy-to-follow order for experience, skills and education. A simple structure helps recruiters and applicant tracking systems find key details.

How can I show Generative AI achievements on my CV?

Use concise bullet points to explain the solution, your contribution and the result. Where you have evidence, include figures or details about deployment, response quality, latency, reliability or operational use.

Should I include a photo on my CV?

For UK applications, a photo is usually not needed. Use the space for relevant skills, experience and measurable results instead.

ATS Score 98%

How we calculate this score

  • Keywords: 60% of the total. AI extracts keywords from your job description. If you do not provide one, a standard job description for the title matching your CV is used. This is not a match to a specific vacancy.
  • Text-based CV: 20%. The text CV assessed here receives 100 for this part.
  • CV quality: 20%. We start at 100 and subtract points for issues found by our CV checks, down to a minimum of zero.
  • Keyword coverage = round(100 × confirmed matches ÷ total keywords). Exact matches and supported equivalents verified by AI receive full credit; unsupported keywords receive none. Live text checks use the saved equivalents and do not request a new AI review. Without keywords, no overall ATS score is available.
  • Final score = 60% of keyword coverage + 20% of the text score + 20% of the quality score, rounded to a whole number. Without keywords, no overall ATS score is available.

What this score means

Our scores are estimates, not employer ratings. They may contain errors and do not guarantee accurate parsing, a ranking, an interview, or a job. Check your document against the employer’s requirements. You are responsible for relying on this score.

Terms and Conditions

Score weights: Keywords 60% · Text based CV 20% · CV quality 20%

Keyword coverage: 23 of 24 (96%) · CV quality: 100%

CV quality 100% · Weight 20% · Issues (0)

Details
  • ✓Name present: Benjamin Ross
  • ✓Email format: benjamin.ross@example.com
  • ✓Phone format: 07700 90XXXX
  • ✓Experience 1: Job title: AI Engineer
  • ✓Experience 1: Company name: Cedarstone Bank
  • ✓Experience 1: Work location: Leeds, West Yorkshire
  • ✓Experience 1: Employment dates: Dec 2023 - Present
  • ✓Experience 1: Description or achievements: Present
  • ✓Experience 2: Job title: Machine Learning Engineer
  • ✓Experience 2: Company name: Harbourline Payments
  • ✓Experience 2: Work location: Bristol
  • ✓Experience 2: Employment dates: Mar 2022 - Nov 2023
  • ✓Experience 2: Description or achievements: Present
  • ✓Experience 3: Job title: Software Engineer
  • ✓Experience 3: Company name: Cairn Mutual
  • ✓Experience 3: Work location: Cardiff
  • ✓Experience 3: Employment dates: Jun 2020 - Feb 2022
  • ✓Experience 3: Description or achievements: Present
  • ✓Experience 4: Job title: Junior Software Engineer
  • ✓Experience 4: Company name: Redbridge Analytics
  • ✓Experience 4: Work location: Nottingham
  • ✓Experience 4: Employment dates: Aug 2018 - May 2020
  • ✓Experience 4: Description or achievements: Present
  • ✓No placeholder fields
  • ✓No repeated achievement bullets
  • ✓No empty bullets

No issues found by the current checks.

Text Based CV 100% · Weight 20%

Parsed text
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)

Matched keywords (23)

  • 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.Original keyword in JD: Production-scale Generative AI solution design, testing and deployment
  • software engineering
  • PythonOriginal keyword in JD: C# OR Python
  • Developed data and model workflows across Azure AI Foundry, Azure Fabric, Azure Data Factory and Azure Synapse AnalyticsOriginal keyword in JD: Azure service experience
  • CosmosOriginal keyword in JD: Azure Fabric OR Data Factory OR ML Studio OR Foundry OR Synapse OR Cosmos
  • Presented design options and technical risks to product, security and engineering colleaguesOriginal keyword in JD: Stakeholder engagement
  • work with product, security and engineering colleagues to shape requirements, test solutions and resolve issues after release.Original keyword in JD: Cross-functional technology collaboration
  • Generative AI
  • Designed and released production-scale Generative AI servicesOriginal keyword in JD: AI/ML solution design
  • machine learning
  • integrating them with existing services and Azure Cosmos DBOriginal keyword in JD: Integration with existing systems
  • Data analysis
  • Monitored model performance after deploymentOriginal keyword in JD: Model performance monitoring
  • 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.Original keyword in JD: Technical issue resolution
  • technical guidance
  • LLM APIs
  • chatbotsOriginal keyword in JD: Chatbots OR agents
  • FastAPI
  • Microsoft Agent Framework
  • LangChain
  • Vector Databases
  • ML Engineering
  • financial services

Missing keywords (1)

  • Scalable model development
Disclaimer: All names, images, contact information, employment histories, achievements, security clearances, military credentials, and other qualifications shown in this content are fictional and used for illustrative purposes only. Any resemblance to actual persons, living or deceased, is purely coincidental.

CV and cover letter examples and recommendations in this article reflect general best practices and professional experience and are provided for guidance only. Results may vary based on role, industry, region, and hiring organisation.

Content Accuracy and Verification: To the fullest extent permitted by applicable law, we do not represent or warrant that CV or cover letter guidance, examples, recommendations, or related information are accurate, complete, current, error-free, or suitable for any particular purpose. You are responsible for independently reviewing and verifying the information before relying on it.

ATS and Cover Letter Scores: ATS scores are estimates calculated using our own formula, informed by publicly available guidance on CV formatting and keyword matching. They are not scores issued or endorsed by an ATS provider or employer. Cover letter scores are also our own assessments. Parsing, weighting, screening criteria, and results vary between systems, employers, job descriptions, and document formats. No score guarantees successful parsing, a particular ranking, an interview, or employment. Use scores as general guidance and independently check your documents against the employer’s requirements. To the fullest extent permitted by applicable law, we accept no liability for errors in scores or parsing, or losses arising from reliance on these assessments. Nothing in this notice excludes liability or limits consumer rights that cannot lawfully be excluded or limited.

Terms and Conditions
 
> JP 1 1
PDF Footer and Margins Setup
The margins are applied to the document, and the footer appears in both the preview and the PDF

Footer Font Settings

Are you applying for a specific job
so we can tailor your CV to it?
Are you applying for a specific job
so we can tailor your cover letter to it?

Your data stays private and is never used for training.Privacy Policy

Type your details as text to generate a personalised CV Type your details as text to generate a personalised cover letter
Website link found! Ready to create CV from:

Your data stays private and is never used for training.Privacy Policy

Drag the into the box to verify you're human.
Drop here

My CVs

Showing {number_of_files} files (out of {total_of_all_files} total)
Name File Type Last Modified: Description:

Rename File

Filename already exists!

Delete Files

Warning: This action is irreversible. Once you click submit, the files will be permanently deleted.

Heading text
Upload From Computer Upload
Select From Existing
LinkedIn
Drag & Drop files anywhere in this tab, or

Uploaded Files

Delete Name Last Updated Use This File
Select this to use the file for generating your CV and cover letter. Only one source—uploaded file, selected file, or LinkedIn text—can be used.

My Files

CVs or cover letters you create will appear here. No files available yet.
Delete Name Last Updated Use This File
Select this to use the file for generating your CV and cover letter. Only one source—uploaded file, selected file, or LinkedIn text—can be used.

Add LinkedIn Profile PDF

You can download your LinkedIn profile as a PDF by opening linkedin.com in a web browser, clicking your profile photo, selecting the “More” or “Resources” button, and choosing “Save to PDF.” You can then attach the PDF using the Upload From Computer tab.

Paste Your LinkedIn Profile Text

If you have copied the LinkedIn profile text, paste it below. See how to copy your profile from LinkedIn

Select this to use the LinkedIn profile text for generating your CV and covering letter. Only one source—uploaded file, selected file, or LinkedIn text—can be used.

Try these controls

<
>