AI Product Manager – Visual Intelligence

Novelis•Atlanta, GA

8d•Hybrid

About The Position

Novelis is one of the world leaders in aluminum recycling and rolling and a leading sustainable aluminum solutions provider. Driven by our purpose of shaping a sustainable world together, we work alongside our customers to provide innovative solutions to the aerospace, automotive, beverage packaging and specialty markets. Headquartered in Atlanta, Georgia, Novelis has approximately 13,000 employees in 32 operating facilities on 4 continents. The AI Product Manager – Visual Intelligence is responsible for leading the product vision, roadmap, and delivery of computer vision and visual intelligence solutions across Novelis’ global manufacturing operations. Reporting to the Head of Data Science, this role is responsible for the end-to-end product lifecycle for visual AI applications—from use case identification and feasibility assessment through deployment, monitoring, and continuous improvement. The AI Product Manager – Visual Intelligence partners with plant operations, quality, and safety partners to translate manufacturing challenges into deployable computer vision systems that drive measurable improvements in quality inspection, safety monitoring, scrap sorting, and process automation at the factory edge. This role ensures that all visual AI products are aligned to Novelis’ enterprise AI safety and governance framework and are engineered to scale reliably across the global footprint.

Requirements

Bachelors degree in Computer Science, Data Science, Engineering, or a related field.
Minimum of 8 years of experience in AI/ML product management, data science, or AI systems delivery.
Demonstrated experience handling AI product lifecycles from concept through production deployment at enterprise scale.
Working knowledge of machine learning, computer vision, predictive modeling, or generative AI technologies.
Strong communication and partner management skills with the ability to translate technical concepts into business language.

Nice To Haves

Master’s degree or advanced certification in AI, Machine Learning, or a related field.
2+ years of experience in a people leadership or team management role.
Experience in manufacturing, industrial, or sustainability-focused organizations.
Familiarity with OT/IoT data, edge computing, or industrial AI deployment environments.
Experience with Novelis or Hindalco technologies and processes.

Responsibilities

Define and lead the product roadmap for assigned AI capability domains, prioritizing use cases with operations and business sponsors and aligning Novelis’ enterprise AI strategy, 3×30 sustainability targets, and digital transformation goals.
Conduct use case discovery, feasibility assessment, and business value analysis to identify and prioritize the highest-impact AI automation opportunities across the global manufacturing footprint.
Translate complex manufacturing and operational challenges into clear product requirements, acceptance criteria, and delivery achievements for AI engineering teams.
Lead the full product lifecycle from concept through deployment, monitoring, and continuous improvement, ensuring products meet production-grade reliability and performance standards.
Partner with plant operations, quality, safety, maintenance, and business partners to translate operational problems into deployable, governed AI solutions that drive measurable improvements.
Communicate product vision, roadmap progress, delivery timelines, and trade-offs to senior leadership and cross-functional partners.
Coordinate with Data Engineering for data pipeline dependencies and with MLOps for production deployment and monitoring requirements.
Ensure all AI products align with the enterprise AI safety and governance framework and are engineered to scale reliably across multiple plant environments.
Align work execution to Novelis’ enterprise strategic data outcomes including trusted data, operational reliability, metal flow optimization, 3×30 sustainability goals, and cash focus/operational efficiency.
Support the enterprise Data & AI Governance framework, ensuring governance is embedded into all workflows and deliverables.
Contribute to quarterly planning, feature scoping, and sprint execution aligned to the enterprise delivery roadmap and critical metric framework.
Hire, develop, and retain team members, fostering a culture of engineering excellence, accountability, and continuous improvement.
Set clear performance expectations, conduct regular performance reviews, and provide ongoing coaching and mentoring.
Define team capacity allocation, and succession planning to ensure operational continuity and talent depth.
Create a supportive team environment that attracts top talent through a compelling vision, clear career growth paths, and professional development opportunities.