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

Apolis
πŸ‡ΊπŸ‡Έ United States
On-site
Staff / Principal
3 weeks ago
$55 – $56 / hour
  • AI
  • AWS Bedrock
  • AWS
  • Python
  • OpenAI
  • React.js
  • Node.js
  • Jenkins
  • GitHub
  • Claude
  • Copilot
  • LangGraph
  • LangChain
  • CrewAI
  • RAG
  • Terraform
  • IaC
  • Bedrock
  • API Gateway
  • IAM
  • VPC
  • CloudWatch
  • FastAPI
  • Flask
  • MCP
  • Model Context Protocol
  • LangSmith
  • AI/ML
  • Machine Learning
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Tech Lead β€” AI Engineering (AWS Bedrock Agent Core)
Onsite (Atlanta, GA :: Hartford, CT ::Β  St.Paul, MN
Pay rate: $55/hr. on W2
6+ months contract

Tech Lead β€” AI Engineering (AWS Bedrock Agent Core)

Mandatory Skillsets: β€―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 β€” tool/function calling, multi-step reasoning, human-in-the-loop patterns Own end-to-end RAG pipeline architecture β€” 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 β€” 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 β€” 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 β€” 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)


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

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