Lead AI/ML Engineer

Lead AI Engineer

Role Summary

Lead the design and delivery of GraphRAG, Retrieval-Augmented Generation (RAG), orchestration, and knowledge graph capabilities for enterprise AI solutions. Provide technical leadership, guide engineering teams, drive architecture decisions, and ensure scalable, production-ready implementations across retrieval, semantic reasoning, and agent-based workflows.

Key Responsibilities

• Lead development and delivery of GraphRAG, RAG, orchestration, and semantic AI capabilities.
• Define technical standards, best practices, and solution architecture for AI feature development.
• Mentor AI Engineers through design reviews, code reviews, and technical guidance.
• Design and optimize prompts, retrieval pipelines, embeddings, and vector search strategies.
• Lead implementation of GraphRAG-based dynamic query generation and graph-aware retrieval.
• Drive knowledge graph schema evolution, ontology mapping, and semantic disambiguation efforts.
• Own integration of retrieval pipelines with agent routing, orchestration, and response generation.
• Collaborate with Architects, Backend Engineers, Product Owners, and Knowledge Graph teams.
• Establish evaluation frameworks, golden datasets, grounding strategies, and quality metrics.
• Define sprint acceptance criteria and ensure successful delivery of AI capabilities.
• Document architecture decisions, implementation patterns, and future fine-tuning roadmaps.

Required Skills & Experience

• 10+ years of software engineering experience with7+ years in AI/ML engineering.
• Strong expertise inPython and enterprise-grade application development.
• 5+ years of hands-on experience withRAG, GraphRAG, LLM applications, and semantic search.
• Proven experience designing and implementing GraphRAG architectures and knowledge graph solutions.
• Deep understanding of vector databases, retrieval pipelines, embeddings, and prompt engineering.
• Experience with SPARQL, ontology management, graph databases, and graph-aware retrieval.
• Strong architecture, system design, and technical leadership experience.
• Experience defining AI evaluation frameworks, golden datasets, and grounding strategies.
• Demonstrated ability to lead technical delivery and mentor engineering teams.

Preferred Qualifications

• Experience building enterprise or regulated AI platforms.
• Hands-on experience withLangGraph, LangChain, Semantic Kernel, AutoGen, or similar frameworks.
• Experience implementing production-scale GraphRAG and agentic AI solutions.
• Familiarity with Azure OpenAI, AWS Bedrock, Vertex AI, or similar AI platforms.
• Experience working with Knowledge Graph governance and validation teams.
• Exposure to pharma, biotech, manufacturing, or scientific data domains.
• Experience authoring architecture documents and technical strategy recommendations.

Education

Bachelor’s or Master’s degree in Computer Science, AI/ML, Data Science, or a related field, or equivalent practical experience.