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.

Job Summary

More about the role

Leads product ownership of enterprise AI and Generative AI solutions built on ChatGPT and LLM platforms, driving adoption, governance, and business value across the AI Champions ecosystem. Acts as the primary technical and functional owner for ChatGPT-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 ChatGPT 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

ChatGPT Product Ownership Own roadmap, prioritization, and lifecycle of ChatGPT-based solutions and GenAI use cases across business functions.
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 agent-based workflows.
Agent / Workflow Lifecycle Management Oversee design, testing, deployment, and monitoring of ChatGPT-powered agents, assistants, and workflows.
Multi-Agent Ecosystem Enablement Guide design and implementation of multi-agent architectures (planning, retrieval, summarization, orchestration) for complex workflows.
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 platform, access, usage, and solution-related issues to ensure smooth operations for AI Champions.
AI Catalogue & Reporting Track AI use cases, adoption, performance, and business impact across ChatGPT-based initiatives.
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.
Stakeholder Management & Communication Collaborate across business, technical, and governance teams and present updates, insights, and recommendations to leadership.
AI Adoption & Community Building Drive enterprise adoption through training, best practices, and active engagement with the AI Champions community.

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 AI/ML or cloud certifications are desirable.
ML & LLM Expertise Strong understanding of ML and LLM concepts including prompt engineering, RAG, agent-based systems, and conversational AI.
ChatGPT / GenAI Platforms Hands-on experience or strong exposure to ChatGPT (enterprise versions), LLM APIs, or similar GenAI platforms.
Product Ownership / Delivery Experience Experience managing product backlog, prioritization, roadmap planning, and stakeholder engagement.
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 for data integration, ML workflows, and enterprise data platforms.
Governance & Compliance Understanding of AI governance frameworks (PIA/BIA, privacy, security, DLP).
Agent / Workflow Lifecycle Understanding Experience or familiarity with designing, deploying, and monitoring AI assistants, workflows, or agent-based systems.
Technical Skills Proficiency in Python and SQL with the ability to evaluate AI outputs, debug issues, and guide improvements.
Leadership & Communication Strong stakeholder management, cross-functional collaboration, and ability to influence adoption at scale.

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.

Lead ML Operations Engineer