Technical Product Owner – Lead AI Engineer

Responsibilities

• Partner with business stakeholders to identify, prioritize, and deliver AI use cases aligned to strategic objectives.
• Act as Technical Product Owner (TPO) for AI products and platforms, managing backlog prioritization and roadmap execution.
• Translate business requirements into actionable technical epics, features, and user stories.
• Drive adoption of AI solutions by ensuring measurable business outcomes and user satisfaction.
• Design, develop, and deploy Machine Learning, Predictive Analytics, Generative AI, and Agentic AI solutions.
• Lead model lifecycle activities including experimentation, training, validation, deployment, monitoring, and continuous improvement.
• Establish engineering best practices covering MLOps, model governance, performance monitoring, and operational support.
• Ensure AI solutions are scalable, secure, maintainable, and compliant with enterprise standards.
• Collaborate closely with Data Engineers to design trusted, reusable, and governed data assets.
• Support the creation of robust data pipelines required for AI development and operationalization.
• Drive integration of structured and unstructured data sources across enterprise platforms.
• Contribute to AI and Data Platform architecture decisions to improve scalability and reuse.
• Lead Agile squads delivering AI products and capabilities across multiple business domains.
• Facilitate sprint planning, backlog refinement, retrospectives, and delivery governance activities.
• Remove delivery obstacles and ensure predictable execution against committed objectives.
• Promote DevOps and Agile best practices across the squad.
• Act as the bridge between business teams, product managers, architects, and engineering teams.
• Ensure AI solutions comply with security, privacy, responsible AI, and regulatory requirements.
• Define and monitor OKRs/KPIs for AI solution performance, business value realization, adoption, and operational effectiveness.

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Artificial Intelligence, or related disciplines.
• 5–7+ years of experience in Data Science, Machine Learning, or AI Engineering roles.
• Demonstrated experience leading the delivery of AI and Analytics solutions in enterprise environments.
• Proven experience acting as Technical Product Owner, Delivery Lead, Lead Engineer, or Squad Lead.
• Strong knowledge of Machine Learning, Generative AI, LLMs, Vector Databases, RAG, and AI agent frameworks.
• Experience working with cloud-based AI ecosystems (Azure, AWS, or GCP).
• Understanding of Data Engineering concepts, including data pipelines, ETL/ELT, data lakes, and data warehousing.
• Experience with Agile methodologies and Scrum delivery frameworks.

Core Competencies: Demonstrates expertise in leading AI product development and delivery, with a strong focus on Machine Learning, Generative AI, and data engineering practices. Capable of translating business needs into technical solutions while ensuring compliance with security and regulatory standards.