Lead ML Operations Engineer

Job Summary

Leads product ownership of enterprise AI and Generative AI solutions built on Copilot and LLM platforms, driving adoption, governance, and business value across the AI Champions ecosystem. Acts as the primary technical and functional owner for Copilot-based solutions, managing the lifecycle of AI use cases and ensuring alignment with enterprise policies and standards.

Works closely with AI Champions, business stakeholders, and engineering teams to enable, support, and scale GenAI solutions. In addition to Copilot ownership, contributes to broader AI initiatives involving AWS and Snowflake-based architectures, ensuring integration with enterprise data platforms and scalable solution design.

Key Areas of Responsibility

• Copilot Product Ownership
  Own roadmap, prioritization, and lifecycle of Copilot-based solutions and GenAI use cases.

• AI Champions Enablement & Support
  Act as the central contact for AI Champions, guiding use case development, onboarding, troubleshooting, and adoption.

• Use Case Identification & Scaling
  Partner with business teams to identify high-impact AI use cases and drive scaling across functions.

• LLM & GenAI Solution Guidance
  Provide expertise in LLM-based solutions including prompt engineering, RAG, conversational AI, and multi-agent workflows.

• Agent Lifecycle Management
  Oversee development, testing, publishing, and monitoring of Copilot agents across environments.

• Multi-Agent / Copilot Ecosystem Enablement
  Guide implementation of multi-agent architectures for complex workflows and decision support.

• Governance, Compliance & Risk
  Ensure adherence to enterprise AI governance (PIA/BIA, security, privacy, DLP policies) and responsible AI practices.

• Issue Management & Operational Support
  Manage and resolve Copilot, agent, licensing, and platform-related issues to ensure smooth operations.

• AI Catalogue & Reporting
  Track AI use cases, agent adoption, performance, and business impact.

• AWS & Snowflake Project Support (Secondary Responsibility)
  Support AI/ML and GenAI projects leveraging AWS and Snowflake, contributing to solution design, data integration, and platform alignment where required.

• Stakeholder Management & Communication
  Collaborate across business, technical, and governance teams and communicate updates to senior leadership.

• AI Adoption & Community Building
  Drive enterprise adoption through training, workshops, and active participation in AI Champions initiatives.

Critical Experiences

• Experience
  Minimum 5+ years of experience in Machine Learning, Data Science, AI Engineering, or related roles, with exposure to GenAI and LLM-based solutions.

• Education & Certifications
  Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or related field. Relevant certifications in AI/ML or cloud platforms are desirable.

• ML & LLM Expertise
  Strong understanding of ML and LLM concepts including prompt engineering, RAG, agent-based systems, and conversational AI.

• Copilot / GenAI Platforms
  Hands-on experience or strong exposure to Microsoft Copilot, Copilot Studio, or similar enterprise GenAI platforms.

• Product Ownership / Delivery Experience
  Experience managing product backlog, prioritization, and stakeholder engagement for AI or digital products.

• AI Champions / Federated AI Model Exposure
  Experience working in federated AI environments or enabling business users to build and scale AI solutions.

• AWS & Snowflake Exposure (Supporting Role)
  Working knowledge or project exposure to AWS and Snowflake, including data integration, ML workflows, and enterprise data platforms.

• Governance & Compliance
  Understanding of AI governance processes (PIA/BIA, security, privacy, DLP).

• Agent Lifecycle & Platform Understanding
  Experience or familiarity with agent development, deployment, environment management, and monitoring.

• Technical Skills
  Proficiency in Python and SQL with ability to analyze data and evaluate AI outputs.

• Leadership & Communication
  Strong stakeholder management and ability to work across business and technical teams.