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 with 7+ years in AI/ML engineering . Strong expertise in Python and enterprise-grade application development. 5+ years of hands-on experience with RAG, 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 with LangGraph, 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.
Job description provided by Milestone Technologies.
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