Lead ML Operations Engineer

Job description

About Signify Through bold discovery and cutting-edge innovation, we lead an industry that is vital for the future of our planet: lighting. Through our leadership in connected lighting and the Internet of Things, we're breaking new ground in data analytics, AI, and smart solutions for homes, offices, cities, and beyond. At Signify, you can shape tomorrow by building on our incredible 125+ year legacy while working toward even bolder sustainability goals. Our culture of continuous learning, creativity, and commitment to diversity and inclusion empowers you to grow your skills and career. Join us, and together, we’ll transform our industry, making a lasting difference for brighter lives and a better world. More about the role 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. Everything we’ll do for you You can grow a lasting career here. We’ll encourage you, support you, and challenge you. We’ll help you learn and progress in a way that’s right for you, with coaching and mentoring along the way. We’ll listen to you too, because we see and value every one of our 27,000+ people. We believe that a diverse and inclusive workplace fosters creativity, innovation, and a full spectrum of bright ideas. With a global workforce present in 70+ countries, we are dedicated to creating an inclusive environment where every voice is heard and valued, helping us all achieve more together. Come join us, and together we can light up the future.