GlobalLogic
Lead AI Engineer
Remote Lead $6.8k–$14.5k/moest.
Summary
GlobalLogic is seeking a Lead AI Engineer to architect and implement an AI-driven SDLC automation platform. This role focuses on designing RAG pipelines, agent systems, and tool-calling mechanisms using AWS Bedrock, with responsibility for establishing AI engineering standards and long-term GenAI roadmap.
What you'll do
- Architect and implement RAG pipelines on AWS Bedrock
- Design knowledge ingestion pipelines from JIRA, GitHub, Confluence, and S3
- Define chunking, embedding, and retrieval strategies
- Design vector storage and retrieval architecture
- Architect tool-calling agent systems using MCP or equivalent architectures
- Implement hallucination mitigation strategies
- Build evaluation pipelines for model quality and regression testing
- Optimize token usage and latency
- Define model routing strategies balancing cost versus quality
- Implement guardrails and structured validation
- Collaborate with DevOps to productionize AI services
- Mentor AI engineers and define AI engineering standards
- Define long-term GenAI roadmap and architecture patterns
Requirements
- 8+ years software engineering experience
- 3+ years hands-on ML/AI engineering experience
- Strong Python (mandatory)
- Proven production experience with LLM systems beyond notebooks or PoCs
- Experience with AWS Bedrock
- Experience designing tool-calling LLM systems (MCP or equivalent architecture)
- Experience integrating external APIs as agent tools
- Experience building REST services (FastAPI or similar)
- Experience with vector databases (OpenSearch, Pinecone, etc.)
- Experience implementing evaluation frameworks for LLM quality
- Experience mitigating hallucinations and prompt instability
- Deep understanding of RAG architecture, embeddings, chunking strategies, and retrieval optimization
- Knowledge of token economics and context window constraints
- Experience integrating with GitHub and JIRA APIs
Conditions
Production-focused role requiring real GenAI experience. Involves mentoring responsibilities and architectural decision-making for company-wide AI engineering standards.