Lead Product Development AI Engineer

We are seeking a Lead Product Development Engineer - Generative & Agentic AI to define, architect, and deliver next-generation GenAI and agentic AI-powered product platforms that drive measurable business and customer impact. This role is designed for highly experienced engineers who have successfully led complex, production-grade GenAI and agentic AI systems and who operate as both a technical authority and a strategic product partner across the organization.

In this role, you will own the architecture and evolution of GenAI, agentic AI, and Model Context Protocol (MCP)-based systems. You will shape the AI roadmap, mentor senior engineers, and ensure that AI capabilities are scalable, secure, cost-efficient, and responsibly deployed across multiple product lines.

About You - experience, education, skills, and accomplishments

• 7 years of experience in software engineering and AI/ML, with proven delivery of GenAI and agent-based systems in real production environments.

• Strong leadership experience building and scaling large, enterprise-grade GenAI solutions embedded into products.

• Expert proficiency in Python, distributed systems, APIs, microservices and overall system design.

• Hands-on expertise with LLMs, agent frameworks (LangChain, AutoGen, CrewAI, LlamaIndex, etc.), and agent orchestration patterns.

• Deep knowledge of RAG architectures, embeddings, vector databases (FAISS, Pinecone, Milvus, Weaviate), and advanced retrieval and evaluation techniques.

It would be great if you also have:

• Experience leading AI copilots, agentic platforms, or multi-product agent-based systems.

• Familiarity with Model Context Protocol (MCP) and context standardization approaches.

• Familiarity with AI governance frameworks, compliance, and regulated environments.

• Contributions to internal AI platforms, open-source projects, or industry thought leadership

What will you be doing in this role:

• Define and drive the technical vision for GenAI, agentic AI and MCP-based capabilities across multiple product lines.

• Lead prompt engineering, memory management and MCP-based context orchestration for scalable AI systems.

• Design and optimize RAG, enterprise knowledge and MCP-backed context platforms, including secure data ingestion and governance.

• Guide the integration of GenAI and agentic AI features into core products, APIs and enterprise platforms.

• Drive production readiness covering reliability, observability, performance, and responsible / safe agent behaviour.

What You'll Build

• Company-wide GenAI, Agentic AI, and MCP-based product platforms

• Scalable RAG, agent orchestration, and context management frameworks

• Enterprise standards for AI quality, safety, and reliability

• A strong technical leadership bench for the next generation of GenAI engineers