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M

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

Mindlance
🇺🇸 United States
On-site
Staff / Principal
3 weeks ago
$73 – $78 / hour
  • AI
  • Machine Learning
  • MLOps
  • AWS
  • Python
  • AWS Bedrock
  • LangGraph
  • LangChain
  • CrewAI
  • RAG
  • Terraform
  • IaC
  • Amazon Bedrock
  • AWS Lambda
  • API Gateway
  • IAM
  • VPC
  • CloudWatch
  • FastAPI
  • Flask
  • Model Context Protocol
  • MCP
  • LangSmith
  • AI/ML
  • OpenAI
  • React.js
  • Node.js
  • Jenkins
  • GitHub
  • Claude
  • Copilot
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Additional Skills Requested for Role

Skill (optional)

Level (optional)

Criteria (optional)

AI Architect

Advanced (6-9 years experience)

Machine Learning Operations (MLOps)

Intermediate (3-5 years experience)

AWS Python

Advanced (6-9 years experience)

AWS Bedrock Engineering

Role: Tech Lead — AI Engineering (AWS Bedrock Agent Core)

Location: Atlanta, GA/Hartford, CT/ St.Paul, MN

Responsibilities:

  • Lead the architecture and technical direction of Agentic AI systems built on AWS Bedrock AgentCore, including Runtime, Gateway, Memory, and Identity components.
  • Design and implement multi-agent orchestration workflows using frameworks such as LangGraph, LangChain, Strands, or CrewAI, incorporating:
  • Tool and function calling
  • Multi-step reasoning
  • Human-in-the-loop workflows
  • Own the end-to-end Retrieval-Augmented Generation (RAG) architecture, including:
  • Data chunking strategies
  • Embedding models
  • Vector database indexing
  • Retrieval optimization and tuning
  • Re-ranking mechanisms
  • Drive and govern Terraform-based Infrastructure as Code (IaC) for AWS AI workloads, including:
  • Amazon Bedrock
  • AWS Lambda
  • API Gateway
  • IAM
  • VPC
  • CloudWatch
  • Build, review, and maintain production-grade Python services using FastAPI and Flask to expose Agentic AI and RAG capabilities.
  • Implement Model Context Protocol (MCP) integrations to enable secure, standardized access for tools, agents, and external systems.
  • Establish and enforce AI evaluation and observability standards using tools such as RAGAS, LangSmith, and custom evaluation frameworks to monitor:
  • Hallucination rates
  • Response quality
  • Latency
  • Cost efficiency
  • Define and implement AI governance and security standards, including:
  • Guardrails and safety controls
  • Prompt injection prevention
  • PII masking and data protection
  • Audit logging and compliance measures
  • Lead technical design reviews, architecture discussions, and code reviews across the AI engineering organization.
  • Mentor and develop a team of AI/ML engineers by:
  • Providing technical guidance
  • Supporting career development
  • Contributing to hiring and talent assessment
  • Serve as the primary technical point of contact for clients and business stakeholders on AI architecture, design decisions, and solution strategies.
  • Balance hands-on technical contributions with leadership responsibilities, remaining an active individual contributor while driving team success and technical excellence.

Required Qualifications:

  • 9+ years of overall software engineering experience, including 3+ years of hands-on experience in production-grade Generative AI and Agentic AI solutions.
  • Direct hands-on experience with AWS Bedrock AgentCore, with the ability to demonstrate and discuss specific implementation use cases and architectures.
  • Strong expertise in Python development and Terraform for infrastructure automation and management.
  • Proven experience in leading engineering teams and/or owning architecture and technical decision-making for large-scale projects.
  • Deep hands-on experience with RAG (Retrieval-Augmented Generation) architectures and agent orchestration frameworks such as:
  • LangGraph
  • LangChain
  • CrewAI
  • Strands
  • Experience working with:
  • Model Context Protocol (MCP)
  • Vector databases
  • LLM evaluation and observability frameworks
  • Demonstrated track record of effectively collaborating with clients, business stakeholders, and cross-functional teams, with strong communication and stakeholder management skills.

Preferred:Insurance/claims domain experience Forward Deployed Engineer (FDE) background AWS certifications (AI Practitioner, Solutions Architect, ML Specialty)

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



EEO:

“Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of – Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans.”

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

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