Additional Skills Requested for Role
Skill (optional) | Level (optional) | Criteria (optional) |
AI Architect | Advanced (6-9 years experience) |
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Machine Learning Operations (MLOps) | Intermediate (3-5 years experience) |
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AWS Python | Advanced (6-9 years experience) |
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AWS Bedrock Engineering |
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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
- 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.