Lead Product Development AI Engineer; Bangalore, India

DR Decisions Resources LLC; Ann Arbor (MI); On-site; USD 180,000 - 240,000; Full time

Job summary

DR Decisions Resources LLC is seeking a Lead Product Development Engineer for GenAI and agentic AI to define and deliver next-generation platforms that power enterprise products. You will own architecture for GenAI/MCP systems, mentor senior engineers, and ensure scalable, secure, cost-efficient deployment across product lines.

This role emphasizes hands-on leadership and cutting-edge AI frameworks to drive measurable business impact.

Qualifications

• 7 years of experience in software engineering and AI/ML with production GenAI deployments.
• Proven leadership building and scaling enterprise GenAI solutions.
• Expert in Python, distributed systems, APIs, and microservices.
• Hands-on with LLMs and agent frameworks (LangChain, AutoGen, CrewAI, LlamaIndex, etc.).
• Deep knowledge of RAG architectures, embeddings, vector databases (FAISS, Pinecone, Milvus, Weaviate), and retrieval techniques.

Responsibilities

• 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.

Skills

Python

Distributed systems

APIs

Microservices

LLMs

Agent frameworks

RAG architectures

Embeddings

Retrieval techniques

Tools

LangChain

AutoGen

CrewAI

LlamaIndex

FAISS

Pinecone

Milvus

Weaviate

Job description

Description

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