Lead MLOps Engineer

Lead product ownership of enterprise AI and Generative AI solutions built on Copilot and LLM platforms for a manufacturing GCC. The role focuses on adoption, governance and business value across the AI Champions ecosystem. AWS- and Snowflake-based AI projects are a secondary responsibility.

Responsibilities

• Own the roadmap, backlog prioritization and lifecycle of Copilot solutions and GenAI use cases. Serve as the primary technical and functional contact for AI Champions, supporting onboarding, troubleshooting and adoption.
• Work with business teams to identify high-impact use cases and scale them across functions. Guide LLM solutions involving prompt engineering, RAG, conversational AI and multi-agent workflows.
• Oversee development, testing, publishing and monitoring of Copilot agents across environments. Support multi-agent architectures for complex workflows and decision support, and resolve agent, licensing and platform issues.
• Ensure solutions follow enterprise AI governance requirements, including PIA/BIA, security, privacy, data loss prevention and responsible AI practices. Maintain an AI use-case catalogue and report agent adoption, performance and business impact.
• Support solution design, data integration and platform alignment for AI/ML and GenAI projects using AWS and Snowflake. Coordinate with engineering, business and governance teams; update senior leadership; and promote adoption through training, workshops and AI Champions initiatives.

Qualifications

• Minimum 5+ years in machine learning, data science, AI engineering or a related role, with exposure to GenAI and LLM solutions. A bachelor’s or master’s degree in computer science, data science, AI or a related field is specified; relevant AI/ML or cloud certifications are desirable.
• Strong understanding of ML, LLMs, prompt engineering, RAG, agent-based systems and conversational AI. Hands-on experience or strong exposure to Microsoft Copilot, Copilot Studio or a similar enterprise GenAI platform.
• Experience with AI product delivery, backlog management and stakeholder engagement; exposure to federated AI environments or enabling business users to scale AI solutions. Familiarity with agent development, deployment, environment management and monitoring; working knowledge or project exposure to AWS, Snowflake and enterprise data integration; and proficiency in Python and SQL.

The position is full-time and hybrid in Bengaluru.