Python AI Engineer, Autonomous Agents Resume Emmanuel Boyd Python AI Engineer, Autonomous Agents (919) 555-XXXX emmanuel.boyd@example.com emmanuelboyd Raleigh, NC 27606 STRENGTHS Structured debugging Traced asynchronous execution faults in workflow experiments and refined test fixtures so other students could reproduce results. Practical collaboration Shared code review and debugging guidance with first-year Python students during weekly peer mentoring sessions. Reusable problem solving Separated workflow steps from task-specific logic in the agent prototype, making experiments easier to adapt to varied requests. Careful evaluation Checked retrieval and tool responses against 40 task scenarios, using observed failures to guide reliability improvements. Open-source contribution Addressed repository bugs and documentation gaps, helping new developers follow setup steps and interpret tests more clearly. SKILLS Python programming Autonomous agents Agent orchestration Backend development REST APIs LLMs and RAG Multi-agent systems Agent memory and tools Database integration Vector databases AI infrastructure Distributed systems Workflow reliability Debugging Open-source contribution SUMMARY Computer science graduate focused on Python AI engineering for autonomous agent platforms, with academic and open-source experience in backend development , agent orchestration, and distributed workflows. Build reusable agent components for memory, tool use, integrations, and multi-agent collaboration , applying software engineering fundamentals , data structures , algorithms, and structured debugging. Develop RAG workflows and API integrations, then test behavior against defined task scenarios to identify failure cases. Use containerized cloud experiments to examine reliability and performance, and contribute documentation and code fixes that make projects easier to reproduce. Project experience includes LangGraph, FastAPI, AsyncIO, MCP, and vector databases. EDUCATION Bachelor of Science in Computer Science North Carolina State University 2026 Raleigh, NC TECHNICAL SKILLS Programming Languages: Python, SQL, JavaScript Python Frameworks: FastAPI, Flask, Django Agent Frameworks: LangGraph, LangChain, CrewAI AI Protocols and Libraries: MCP, OpenAI API, Hugging Face Transformers Async and API Tools: AsyncIO, HTTPX, Uvicorn Databases: PostgreSQL, SQLite, Redis Vector Databases: Chroma, FAISS, Pinecone Containers and Orchestration: Docker, Kubernetes, Helm Cloud Platforms: AWS, Microsoft Azure, Google Cloud Platform Linux and Development Tools: Linux, Git, GitHub Actions Testing Tools: pytest, unittest, Postman SKILLS Python programming Autonomous agents Agent orchestration Backend development REST APIs LLMs and RAG Multi-agent systems Agent memory and tools Database integration Vector databases AI infrastructure Distributed systems Workflow reliability Debugging Open-source contribution EXPERIENCE Python AI Engineer, Autonomous Agent Capstone Project University Capstone Studio Jan 2026 - May 2026 Raleigh, NC Built a Python agent orchestration prototype with LangGraph, FastAPI, and AsyncIO, separating reusable workflow steps from task-specific logic to support varied enterprise-style request scenarios. Developed RAG flows using LLMs and a vector database , connecting agent memory and tool calls to database records, REST APIs, and simulated external services; checked responses against a curated set of 40 task scenarios. Implemented an MCP tool server and a CrewAI multi-agent experiment, documenting integration patterns and comparing task outcomes to identify failure cases and guide improvements to reliability and developer experience . Defined reusable platform components and API contracts for simulated enterprise system integrations , then added validation tests for database and external service responses to make workflow changes easier to evaluate. Autonomous Agent Workflow Research Project University AI Systems Lab Aug 2025 - Dec 2025 Raleigh, NC Prototyped distributed workflow orchestration in Python and LangChain, investigating how independent agent steps could exchange state and recover from tool errors in multi-stage tasks. Containerized the test environment with Docker and deployed a small Kubernetes lab setup on a cloud platform, using Linux-based logs and repeatable runs to examine reliability and performance across 25 workflow scenarios. Applied debugging and structured problem-solving to trace asynchronous execution faults, then refined workflow documentation and test fixtures to make experiments easier for other students to reproduce. Python AI Engineer, Open-Source and Personal AI Projects University Software Engineering Clinic Jan 2025 - May 2025 Raleigh, NC Created a FastAPI backend for a personal Python AI assistant, using REST APIs and database persistence to connect user requests with a small set of external services. Contributed documentation and bug fixes to public Python open-source repositories, applying data structures, algorithms, code review feedback, and software engineering fundamentals to improve test clarity and setup for new developers. LEADERSHIP, AWARDS & RECOGNITION Finalist, Undergraduate Project Showcase, North Carolina State University, 2026. Dean's List, North Carolina State University, 2024-2026. Peer mentored introductory Python students through weekly code reviews and debugging guidance, 2025-2026. Coordinated campus computer science group workshops on APIs and collaborative open-source contribution, 2025. CERTIFICATIONS AWS Academy Cloud Foundations, AWS Academy 2025 Python for Everybody Specialization, Coursera 2024 PROFESSIONAL AFFILIATIONS Member, Association for Computing Machinery, participating in a professional community focused on computing and software development. Member, Python Software Foundation, participating in a professional community for Python developers and open-source software.
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