Lead AI Engineer

GlobalLogic is seeking a Lead AI Engineer to design and implement an AI-driven SDLC automation platform leveraging AWS Bedrock, knowledge bases, and domain agents. This role requires extensive production GenAI experience to architect RAG pipelines, agent systems, and tool-calling mechanisms for real-world applications.

• 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
• Design and implement structured output agents
• Implement hallucination mitigation and prompt stability strategies
• Build evaluation pipelines for model quality and regression testing
• Optimize token usage and latency across systems
• Define model routing strategies balancing cost versus quality
• Implement guardrails and structured validation
• Work closely with DevOps to productionize AI services
• Mentor AI engineers and define AI engineering standards
• Define long-term GenAI roadmap and architecture patterns

• 8+ years software engineering experience
• 3+ years hands-on ML/AI engineering experience
• Strong Python proficiency (mandatory)
• Proven production experience with LLM systems
• Experience with AWS Bedrock
• Experience designing tool-calling LLM systems (MCP or equivalent)
• 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
• Experience integrating with GitHub and JIRA APIs
• Production experience beyond notebooks or POCs
• Deep understanding of RAG architecture, embeddings, chunking strategies, and retrieval optimization
• Strong understanding of token economics, context window constraints, and cost-performance tradeoffs

• Culture of caring with inclusive environment and meaningful connections with collaborative teammates
• Continuous learning and development with Career Navigator tool and training programs
• Opportunity to work on cutting-edge and impactful solutions
• Balance and flexibility with multiple functional career areas and work arrangements
• High-trust organization prioritizing integrity and ethical practices