Senior Product Manager - Engineering, EHS & Sustainability

Overview

Own the product vision, roadmap and investment case for an assigned product or capability area within GSK's Enterprise Systems, supporting Engineering (asset management and capital projects management), EHS, or Sustainability.

What you'll do

• Partner with Business Process Owners, functional leaders and users to understand strategic priorities, process pain points and unmet needs, and translate these into clear product outcomes.
• Define and maintain the product vision, strategy and roadmap for an assigned product or capability area, aligned to domain strategy and enterprise technology direction.
• Develop outcome-based investment proposals and contribute to business cases by defining value hypotheses, costs, benefits, risks, assumptions, dependencies and measures of success.
• Set prioritisation guardrails for Product Owners and make roadmap trade-offs based on value, cost, urgency, risk, compliance, operational continuity, capacity and technical dependencies.
• Guide Product Owners and delivery teams so that epics, features and releases remain aligned to product outcomes.
• Partner with Solution and Enterprise Architects to assess solution options and ensure designs are secure, integrated, scalable, supportable and aligned to architecture and data standards.
• Establish and review product performance measures covering adoption, process outcomes, stability, service effort, user experience, delivery flow and benefit realisation; use insights to adjust priorities.
• Ensure product initiatives comply with required governance for cyber security, data protection, quality, validation, change control, service readiness, continuity and records management.
• Lead product-level vendor and solution evaluations using transparent, capability-led criteria and contribute to commercial decisions, supplier performance reviews and lifecycle planning.
• Manage product risks, technical debt, dependencies and obsolescence, ensuring decisions and escalations are documented and addressed through the appropriate governance forums.
• Drive adoption and operational readiness by ensuring business change, training, support model, documentation, release communications and onboarding needs are reflected in plans.
• Promote iterative, user-centred and data-led ways of working and create a culture focused on measurable outcomes, learning, simplification and continuous improvement.
• Identify and prioritise AI opportunities based on business value, user needs, data readiness, technical feasibility, risk and total cost of ownership.
• Define the product vision, roadmap, outcomes and investment case for AI-enabled capabilities across Engineering, EHS and Sustainability.
• Lead AI initiatives from discovery and experimentation through delivery, adoption, scaling and benefits realisation.
• Define measurable success criteria for AI products, including business outcomes, adoption, user experience, output quality, reliability and operational impact.
• Ensure AI-enabled products meet responsible AI, cybersecurity, privacy, validation, human-oversight and service-readiness requirements.

What you'll need

• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, Data Science, Business, Life Sciences or a related discipline, or equivalent relevant experience.
• Typically 5+ years of experience in product management, digital transformation, technology delivery, business systems, manufacturing technology, supply chain technology or a related discipline.
• Proven experience developing a product vision and roadmap for a product, platform or defined capability area.
• Proven experience in the following business domains: Engineering: Plant Maintenance, Calibration, Validation; Content Management, Capital Project Management. EHS: Incident & Accident Management, Occupational Health, Industrial Hygiene, Chemical Compliance. Sustainability: Energy Efficiency, Renewable and Clean Energy, Waste Management.
• Experience translating business priorities and user needs into product outcomes, investment proposals and delivery priorities.
• Experience working with Product Owners and cross-functional delivery teams throughout discovery, design, delivery, release, adoption and operation.
• Demonstrated ability to prioritise based on value, cost, risk, compliance, operational impact, resource capacity and technical dependencies.
• Experience defining product measures and using adoption, process, stability, service and user-experience insights to improve performance.
• Experience contributing to business cases, forecasting costs, tracking benefits and supporting funding decisions.
• Experience operating within governance requirements covering architecture, cyber security, data protection, quality, validation, change and service readiness.
• Experience evaluating suppliers or solution options and managing vendor contributions to product outcomes.
• Experience influencing senior functional stakeholders in a global matrix organisation.
• Experience developing product strategies, roadmaps or business cases for AI-enabled, data-driven or advanced analytics products.
• Experience leading cross-functional teams spanning Product, Engineering, Data/ML, Cyber Security, Compliance and business SMEs.
• Experience taking AI-enabled features from discovery and experimentation through release, adoption and scale-up.
• Experience defining value hypotheses, success measures and acceptance criteria for AI use cases.
• Hands-on experience using AI tools, such as Copilot, AI assistants, analytics or experimentation platforms, to support product discovery, backlog refinement and stakeholder communication.

Nice to have

• Professional certifications in product management, agile delivery, portfolio management, finance or change leadership.
• Strong strategic thinking with the ability to convert ambiguous business challenges into clear product choices and roadmaps.
• Strong communication, facilitation and influencing skills across business, technical and operational audiences.
• Commercial and financial acumen, including the ability to evaluate cost, value, benefits, risk and total cost of ownership.
• Ability to use data and evidence to challenge assumptions, prioritise investment and evaluate product performance.
• Working understanding of enterprise architecture, integration, data, cyber security, validation, service and operational resilience.
• Ability to create alignment across teams with different objectives, cultures, geographies and levels of technical knowledge.
• Strong judgement, accountability and escalation discipline, with a clear understanding of decision rights.
• Commitment to technology-agnostic, capability-led evaluation and to simple, reusable and supportable solutions.
• Experience leading cross-functional squads (product, engineering, data/ML, security, compliance) to deliver AI-driven features from discovery through scale-up.
• Strong understanding of generative AI, machine learning, intelligent automation and analytics from a product-management perspective.
• Ability to assess whether a business problem is appropriate for AI or would be better addressed through process simplification, rules, automation or conventional technology.
• Ability to translate Engineering, EHS and Sustainability needs into clear AI product outcomes, use cases and roadmap priorities.
• Understanding of AI-specific product risks, including inaccurate outputs, poor data quality, inappropriate automation, limited explainability and user over-reliance.
• Ability to define and use business, adoption, quality, risk and operational measures to evaluate AI product performance.

Details

• Location: Bengaluru, Luxor North Tower.