Machine Learning / AI Contractor: 6-9 years (Advanced)

9+ years software engineering experience; 3+ years hands-on production GenAI/agentic AI Direct hands-on experience with AWS Bedrock AgentCore — must be able to speak to specific implementations Strong Python and Terraform expertise Proven experience leading engineers or owning architecture decisions for a team Deep RAG and agent orchestration framework experience. (LangGraph/LangChain/CrewAI/Strands) Experience with MCP, vector databases, and LLM evaluation frameworks Track record of client-facing or cross-functional stakeholder communication Preferred: Insurance/claims domain experience Forward Deployed Engineer (FDE) background AWS certifications (AI Practitioner, Solutions Architect, ML Specialty).

Tech Lead — AI Engineering (AWS Bedrock Agent Core)
Onsite (Atlanta, GA :: Hartford, CT ::  St.Paul, MN
Pay rate: $55/hr. on W2
6+ months contract

Tech Lead — AI Engineering (AWS Bedrock Agent Core)

Mandatory Skillsets: AWS agent Core, Python, OpenAI with LLM, ReactJS, NodeJS, Jenkins, GitHub, Claude, Copilot

Responsibilities:
Lead architecture and technical direction for agentic AI systems built on AWS Bedrock AgentCore (Runtime, Gateway, Memory, Identity) Design multi-agent orchestration workflows using LangGraph, LangChain, Strands, or CrewAI — tool/function calling, multi-step reasoning, human-in-the-loop patterns Own end-to-end RAG pipeline architecture — chunking, embeddings, vector indexing, retrieval tuning, reranking Drive Terraform-based infrastructure-as-code strategy for AWS AI workloads (Bedrock, Lambda, API Gateway, IAM, VPC, CloudWatch) Build and review production Python services (FastAPI/Flask) exposing agent and RAG capabilities Implement MCP (Model Context Protocol) integrations for secure, standardized tool/agent access Establish evaluation and observability standards (RAGAS, LangSmith, custom eval harnesses) for hallucination detection, latency, and cost tracking Set AI governance standards — guardrails, prompt-injection defense, PII masking, audit logging Lead technical design reviews, architecture decisions, and code reviews across the AI engineering team Mentor and grow a team of AI/ML engineers; own hiring input and technical career development Act as primary technical point of contact with client/business stakeholders on AI architecture decisions Balance hands-on coding with team leadership — expected to remain a strong individual contributor while leading Required

Qualifications:
9+ years software engineering experience; 3+ years hands-on production GenAI/agentic AI Direct hands-on experience with AWS Bedrock AgentCore — must be able to speak to specific implementations Strong Python and Terraform expertise Proven experience leading engineers or owning architecture decisions for a team Deep RAG and agent orchestration framework experience
(LangGraph/LangChain/CrewAI/Strands) Experience with MCP, vector databases, and LLM evaluation frameworks Track record of client-facing or cross-functional stakeholder communication Preferred: Insurance/claims domain experience Forward Deployed Engineer (FDE) background AWS certifications (AI Practitioner, Solutions Architect, ML Specialty)