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I’m a senior Python and AI/LLM engineer with 11+ years of experience building scalable backend systems and AI-driven applications across healthcare, banking, and enterprise environments. I work on high-performance APIs, async services, and data-intensive platforms, with a strong focus on Python (FastAPI/Flask/Django), Pydantic validation, and reliable system integration. I also build agentic and retrieval-augmented generation (RAG) workflows using LangChain/LangGraph, vector embeddings, and guardrailed, structured outputs for safer, more accurate results. Recently, I’ve delivered telecom and compliance document automation, orchestration for multi-step agent tasks, and monitoring/evaluation pipelines to improve quality over time while deploying production services on AWS with Docker/Kubernetes and CI/CD.…I’m a senior Python and AI/LLM engineer with 11+ years of experience building scalable backend systems and AI-driven applications across healthcare, banking, and enterprise environments. I work on high-performance APIs, async services, and data-intensive platforms, with a strong focus on Python (FastAPI/Flask/Django), Pydantic validation, and reliable system integration. I also build agentic and retrieval-augmented generation (RAG) workflows using LangChain/LangGraph, vector embeddings, and guardrailed, structured outputs for safer, more accurate results. Recently, I’ve delivered telecom and compliance document automation, orchestration for multi-step agent tasks, and monitoring/evaluation pipelines to improve quality over time while deploying production services on AWS with Docker/Kubernetes and CI/CD.

John AGenAI Engineer

AI Engineer, Back-End Developer, Software Engineer, +2

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I’m a senior Python and AI/LLM engineer with 11+ years of experience building scalable backend systems and AI-driven applications across healthcare, banking, and enterprise environments. I work on high-performance APIs, async services, and data-intensive platforms, with a strong focus on Python (FastAPI/Flask/Django), Pydantic validation, and reliable system integration. I also build agentic and retrieval-augmented generation (RAG) workflows using LangChain/LangGraph, vector embeddings, and guardrailed, structured outputs for safer, more accurate results. Recently, I’ve delivered telecom and compliance document automation, orchestration for multi-step agent tasks, and monitoring/evaluation pipelines to improve quality over time while deploying production services on AWS with Docker/Kubernetes and CI/CD.…I’m a senior Python and AI/LLM engineer with 11+ years of experience building scalable backend systems and AI-driven applications across healthcare, banking, and enterprise environments. I work on high-performance APIs, async services, and data-intensive platforms, with a strong focus on Python (FastAPI/Flask/Django), Pydantic validation, and reliable system integration. I also build agentic and retrieval-augmented generation (RAG) workflows using LangChain/LangGraph, vector embeddings, and guardrailed, structured outputs for safer, more accurate results. Recently, I’ve delivered telecom and compliance document automation, orchestration for multi-step agent tasks, and monitoring/evaluation pipelines to improve quality over time while deploying production services on AWS with Docker/Kubernetes and CI/CD.

Available to hire

I’m a senior Python and AI/LLM engineer with 11+ years of experience building scalable backend systems and AI-driven applications across healthcare, banking, and enterprise environments. I work on high-performance APIs, async services, and data-intensive platforms, with a strong focus on Python (FastAPI/Flask/Django), Pydantic validation, and reliable system integration.

I also build agentic and retrieval-augmented generation (RAG) workflows using LangChain/LangGraph, vector embeddings, and guardrailed, structured outputs for safer, more accurate results. Recently, I’ve delivered telecom and compliance document automation, orchestration for multi-step agent tasks, and monitoring/evaluation pipelines to improve quality over time while deploying production services on AWS with Docker/Kubernetes and CI/CD.

Skills

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Expert

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Intermediate

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Intermediate

Work Experience

Gen A.I / LLM Engineer at Crown Castle (Telecom)

March 1, 2025 - Present

Developed an AI/LLM proof-of-concept pipeline to convert 6,000 compliance documents from Word to PDF. Built agentic AI solutions and end-to-end RAG pipelines including ingestion/parsing, tokenization and chunking, embeddings, vector indexing, retrieval with metadata filtering and re-ranking, prompt construction, and structured response generation. Implemented telecom-focused chunking/token optimization for better contextual retrieval. Used Claude and Qwen for OCR-style extraction to enrich JSON with image-derived descriptions. Curated triplet datasets (anchor/positive/negative) to fine-tune and deploy embedding workflows, storing embeddings in Pinecone for semantic search. Built LLaMA 3.2 RAG question-answering for document-based navigation and extraction. Engineered FAISS/Hugging Face-based autonomous analysis agents to identify relevant document sections and respond accurately with traceable retrieval context, and established monitoring/fine-tuning practices based on outputs and feed

Senior AI/ML Engineer at Elevance Health

April 1, 2024 - March 1, 2025

Built agentic AI workflows that support reasoning, tool selection, API invocation, task execution, and multi-step orchestration for business process automation. Integrated foundation models/LLM APIs with prompt engineering, structured outputs, context management, function/tool calling, and response validation. Designed and deployed scalable AI/ML applications using AWS services (S3, Lambda, EC2, RDS, CloudWatch) and containerized workloads. Implemented Snowflake-based ETL/ELT architectures and high-volume data pipelines. Developed asynchronous REST APIs and microservices with FastAPI/Flask, Pydantic, async/await, and secure JWT/OAuth2 authentication. Added LangSmith and monitoring/tracing for LLM observability and production troubleshooting. Built document indexing and retrieval chains using LangChain/LlamaIndex with enterprise data/API integration, and created guardrails to reduce hallucinations and prompt-injection risks. Developed front-end experiences in React/TypeScript connected

Senior Python Developer (Backend) at BNY Mellon

March 1, 2023 - March 1, 2024

Developed scalable backend services and microservices with Python, Django, and FastAPI to support high-volume financial transactions. Designed secure RESTful APIs using JWT/OAuth2 authentication and asynchronous processing. Built multi-agent AI systems using LangGraph and CrewAI for planning/reasoning/tool calling and orchestrated task execution to streamline enterprise workflows. Applied domain-driven design (DDD) for modular, maintainable backend architecture. Optimized relational data access (indexing/query tuning/ORM patterns) to reduce execution time by ~30%. Integrated LLM-based document processing and semantic search over financial records using embeddings. Supported the ML lifecycle including evaluation, deployment, monitoring, and workflow orchestration, and delivered connected React/TypeScript frontends for real-time dashboards. Deployed containerized services with Docker and automated CI/CD using Jenkins/GitHub Actions, improving release cycles by ~40%.

Python Developer (Backend & API Development) at Bacancy Technology

February 1, 2016 - March 1, 2020

Contributed to full lifecycle application development (requirements, design, coding, testing, and post-deployment support). Built scalable backend business logic and REST APIs for data exchange across frontends and backend systems. Designed dynamic UI experiences with web technologies and implemented database schemas and optimized queries for application needs. Processed and transformed datasets using Python for reporting/analytics, supporting consistent and reliable data preparation. Developed agentic workflows with memory/context management and human-in-the-loop validation, and built RAG-based agent solutions for enterprise knowledge retrieval and context-aware responses. Improved response times (~20%) through performance tuning, and reduced manual effort (~30%) via automation scripts. Integrated backend services with external systems for interoperability and implemented validation and edge-case handling to improve reliability. Participated in Agile delivery and cross-team coordinati

Junior Python Developer at Capital Numbers Infotech

January 1, 2012 - February 1, 2016

Built Python batch processing jobs to extract, transform, and load data into databases with consistent processing across workflows. Developed automation scripts for parsing, file handling, and report generation to reduce manual intervention. Worked on data pipelines supporting real-time and batch feeds for application requirements. Improved backend logic for a real-time bidding platform through performance optimization. Implemented server-side processing for JSON/XML data exchange between system components. Assisted with authentication mechanisms (SSO and directory-based access control), debugging, and defect resolution. Contributed to feature delivery and testing in collaboration with team members and supported ongoing application enhancement after releases.