AI Product Lead – Pinda Unit or CSC
总体的看法:货物位置概述 本职位负责领导 Novelis 全球制造业务中 AI 解决方案产品愿景,路线图,优先级和生命周期管理,主要关注视觉智能,计算机视觉,机器学习和预测分析使用案例。向人工智能自动化与启用主管报告,该职位拥有从使用情况发现,可行性评估,优先考虑,规划,后备管理,发布定义,部署,监控,采用和持续改进的端到端产品流程。这是一个实践领导角色,结合了 产品拥有直接的人员管理,领导一个负责构建和维持人工智能解决方案的开发人员团队.AI Product Lead 与工厂运营,质量,安全,维护,数据工程,MLOps 和软件工程团队密切合作,将制造挑战转化为实用,可扩展的人工智能产品。由于这个角色设定了技术方向并支持工程团队的增长,因此对人工智能,ML,计算机视觉或软件解决方案构建实践经验是强烈的优先。能力配合这一职位符合人工智能自动化和启动支柱,并且拥有或贡献以下企业能力:·计算机视觉和边缘 AI ·代理与自主系统 ·机器学习和预测分析关键责任产品视觉和路线图 ·定义并维护分配的人工智能能力领域的产品路线图,优先考虑使用情况 · 与运营和业务赞助商以及确保符合 Novelis 的企业人工智能战略,·生产优先事项和可衡量的业务价值。·进行实用案例发现,可行性评估和业务价格分析以确定和 ·优先确定全球制造足迹中影响最高的人工智能自动化机会。·将制造和运营挑战转化为明确的产品要求,接受标准和发布计划,平衡交付速度与质量,治理性和长期可支持性。·从概念开始拥有产品后备物流和完整生命周期,通过生产部署,监测和持续改进,提供进展,风险,依赖性和折衷情况的可见性。利益相关者合作伙伴关系和交付 · 与工厂运营,质量,安全,维护和业务利益相关者进行合作。
查看英文原文
Visão geral do cargo
Position Overview
This role is responsible for leading the product vision, roadmap, prioritization, and lifecycle management of
AI solutions across Novelis' global manufacturing operations, with a primary focus on visual intelligence,
computer vision, machine learning, and predictive analytics use cases. Reporting to the Head of AI
Automation & Enablement, this role owns the end-to-end product flow—from use case discovery,
feasibility assessment, prioritization, planning, backlog management, release definition, deployment,
monitoring, adoption, and continuous improvement. This is a hands-on leadership role that combines
product ownership with direct people management, leading a team of developers responsible for building
and sustaining AI solutions. The AI Product Lead partners closely with plant operations, quality, safety,
maintenance, data engineering, MLOps, and software engineering teams to translate manufacturing
challenges into practical, scalable AI products. Because this role sets technical direction and supports the
growth of an engineering team, hands-on experience building AI, ML, computer vision, or software
solutions is strongly preferred.
Capability Alignment
This role is aligned to the AI Automation & Enablement pillar and owns or contributes to the following
enterprise capabilities:
- Computer Vision & Edge AI
- Agentic & Autonomous Systems
- Machine Learning & Predictive Analytics
Key Responsibilities
Product Vision & Roadmap
- Define and maintain the product roadmap for assigned AI capability domains, prioritizing use cases
- with operations and business sponsors and ensuring alignment with Novelis' enterprise AI strategy,
- manufacturing priorities, and measurable business value.
- 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 manufacturing and operational challenges into clear product requirements, acceptance
- criteria, and release plans, balancing delivery speed with quality, governance, and long-term
- supportability.
- Own the product backlog and full lifecycle from concept through production deployment, monitoring,
- and continuous improvement, providing visibility into progress, risks, dependencies, and trade-offs.
Stakeholder Partnership & Delivery
- Partner with plant operations, quality, safety, maintenance, and business stakeholders to translate
- operational pain points 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, Master Data Management, and Data Quality teams to align data
- dependencies, standards, ownership, and readiness, and with MLOps for production deployment and
- monitoring requirements.
- Ensure all AI products comply with the enterprise AI safety and governance framework and are
- engineered to scale reliably across multiple plant environments.
Strategic Traceability & Enterprise Alignment
- 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.
Team Leadership & Development
This role directly manages a team of developers and is accountable for both product outcomes and team
performance, growth, and engagement, specifically:
- Lead. Manage, coach, and develop a team of developers, including goal setting, regular one-on-ones,
- performance feedback, career development, and workload balancing across projects.
- Empower. Provide clear priorities, technical direction, and decision-making support while giving
- engineers ownership over solution design, implementation choices, and technical quality.
- Act with intention. Maintain team focus on product outcomes, adoption, value realization, and
- responsible delivery, balancing speed, quality, governance, and long-term supportability.
Accountability Boundaries
IT owns the AI systems, their engineering, operation, and guardrails; operations and business partners
own the business rules, thresholds, and decisions those systems execute. This role does not own core
data platforms, ingestion pipelines, business KPI definitions, performance reporting dashboards, data
governance rules, MDM policy, or data access configuration.
Responsabilidades e qualificações
Qualifications:
- Bachelors degree in Computer Science, Data Science, Engineering, or a related field.
- Experience across AI/ML product management, data science, software engineering, computer vision, predictive analytics, or AI systems delivery.
- Demonstrated experience leading AI product or solution lifecycles from discovery and planning through production deployment, adoption, monitoring, and continuous improvement.
- Experience leading technical teams, including direct people management or formal team leadership of developers, data scientists, or engineers.
- Experience applying agile product management practices, such as backlog management, prioritization,
- release planning, acceptance criteria definition, and progress visibility; formal Scrum Master experience is helpful but not required.
- Working knowledge of machine learning, computer vision, predictive modeling, software development,
- MLOps, or related AI technologies, with enough technical depth to challenge assumptions and guide
- delivery trade-offs.
- Strong communication and stakeholder management skills, with the ability to translate technical
- concepts into business language and connect business needs, feasibility, delivery capacity, and value
- into clear product decisions.
Preferred Qualifications:
- Master's degree or advanced certification in AI, Machine Learning, or a related field.
- Prior hands-on experience developing AI, machine learning, computer vision, predictive analytics, data
- products, or software solutions before transitioning into product management, delivery leadership, or
- team management.
- Practical experience with computer vision, visual inspection, edge AI, image processing, industrial ML,
- or production analytics solutions.
- 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.
Perfil da localização
Novelis is the world's largest recycler of aluminum and a global leader in rolled aluminum products. We are committed to delivering sustainable solutions across the aerospace, automotive, beverage packaging, and specialty markets. Headquartered in Atlanta, Georgia, Novelis operates 32 facilities across 4 continents and employs approximately 13,000 people. Our purpose—"shaping a sustainable world together"—guides everything we do, from innovation to operations to community engagement.
Originally posted on Himalayas