Pre-screened and vetted in North Carolina.
Junior AI Engineer specializing in LLM pipelines, RAG, and computer vision
“Built and deployed an on-prem, HIPAA-compliant LLM pipeline for oncology-focused clinical note generation and decision support, emphasizing grounded differential diagnosis and explainable reasoning via RAG to reduce hallucinations. Also created a LangGraph-based multi-agent academic paper search system integrating Tavily, arXiv, and Semantic Scholar with an orchestrator that routes tasks to specialized sub-agents.”
Mid-level Software Engineer specializing in AI-driven backend and full-stack FinTech systems
Mid-level Full-Stack Software Engineer specializing in AI platforms and microservices
“Backend engineer currently building an AWS Lambda/FastAPI inventory recommendation system using a LangChain + GPT-4 RAG pipeline and MongoDB vector search; drove major cost optimization via Redis caching (60% reduction) while sustaining 10k+ daily requests under 2s latency. Previously deployed Node.js microservices on AWS OpenShift with Jenkins/Helm at UnitedHealth Group and led a zero-downtime monolith-to-microservices migration at Verizon, including RabbitMQ-based real-time messaging with DLQs and idempotency.”
Mid-level Applied AI Engineer specializing in agentic LLM workflows
“AI engineer with production experience building a LangGraph-based, stateful multi-agent system at MetLife to automate complex insurance claims adjudication, integrating document discovery, Azure Document Intelligence OCR/extraction, and health data analysis. Strong in agent orchestration and production deployment (Docker + FastAPI REST APIs), with a structured approach to reliability, evaluation, and stakeholder-driven requirements.”
Mid-level AI Engineer specializing in Generative AI, RAG, and agentic workflows
Mid-level AI/ML Engineer specializing in LLM systems, MLOps, and real-time fraud detection