The Lead Product Manager AI & Automation is accountable for shaping, scaling and operating AI‑ and automation‑driven digital products that
materially improve Finance effectiveness, efficiency, compliance and decision quality.
The role ensures that AI and intelligent automation are applied where they create measurable business value, reduce manual effort,
strengthen regulatory and internal-control processes , and enable Finance users to focus on value‑adding activities rather than transactional work.
Lead Product Managers operate at strategic and system level. They own a complex ecosystem of AI‑ and automation‑enabled
products spanning multiple Finance processes for financial planning, Record-2-Decide etc., data platforms and squads, and are accountable for aligning business outcomes, technology, data, governance, and people across the end‑to‑end lifecycle.

Your Responsibilities

Product Management

The Lead Product Manager is accountable for the overall success of a portfolio of AI‑ and automation‑enabled digital products throughout
their lifecycle, from conception to decommissioning. The Lead Product Manage owns multiple and/or complex digital products (ecosystem) for
a defined Finance functional area and ensures that these products deliver measurable business value, operational efficiency and compliance.
Lead Product Managers collaborate closely with product development, data, AI, Finance, risk, legal and operations teams to ensure cohesive
delivery, stable operations and consult in AI regulations / compliance. They drive agile best practices across squads, including continuous
planning, backlog prioritization and co‑creation of user stories aligned with strategic outcomes. In addition, Lead Product Managers actively
assess value potential, adoption, performance and lifecycle decisions (e.g. scaling, standardization or retirement). In this role, the Lead
Product Manager provides architectural guidance and drives product and delivery enablement for solutions owned by other squads across
the IT Finance platform.

Stakeholder Engagement

The Lead Product Manager bridges the business, technology, data and AI worlds, ensuring that digital products support Finance strategy and
enterprise objectives. They identify and actively manage a diverse stakeholder landscape, including senior Finance leadership, process owners, data and AI teams, architecture and risk functions. Main stakeholder groups for this role are Divisional Finance, Group Finance and
GBS Finance as large community of users.
While many perspectives and expectations exist, the Lead Product Manager exercises strong judgment to balance innovation, feasibility, risk
and value realization. Stakeholders trust the Lead Product Manager to understand their needs, transparently manage trade‑offs and reliably
deliver solutions that create sustainable value for Bayer.

Product Strategy

The Lead Product Manager defines and drives the product vision, strategy and roadmap for a complex ecosystem of AI‑ and
automation‑enabled products. With full end‑to‑end ownership, they ensure alignment between business priorities, data readiness, technology
platforms and governance requirements.
They provide strategic leadership by planning and optimizing capabilities to achieve business outcomes in the most efficient and scalable
way, applying strong decision‑making and influencing skills to balance user needs, operational stability and long‑term platform sustainability.

Product Discovery & Delivery

The Lead Product Manager is responsible for structured discovery and delivery of digital products, translating user needs and non‑functional
requirements into clear roadmaps and prioritized backlogs. They oversee progress against defined outcomes (e.g. 90‑day objectives), overall
product health and budget responsibilities.
Using Design Thinking and outcome‑driven discovery methods, the Lead Product Manager validates solutions through usability, feasibility,
business fit, risk and value testing. User feedback and performance metrics are continuously monitored to refine solutions, improve adoption
and maximize business impact.

People & Collaboration

Lead Product Managers proactively communicate and collaborate across cross‑functional teams, fostering strong working relationships with
peers in product management, engineering, data and other technical organizations. Effective collaboration across disciplines is essential to
deliver scalable, high‑quality products.
Drives change management and user adoption strategies in collaboration with Finance transformation and communications teams,
recognizing that AI-enabled products often require significant behavioural change
At a lead level, Lead Product Managers also mentor and coach junior product managers, strengthening product management capabilities,
agile practices and outcome orientation across the broader community.

Who You Are

• Bachelor’s degree in Computer Science, Engineering, Business Informatics or comparable experience
• 8+ years of experience in Product Management in complex digital environments
• 4+ years experience working in Agile / DevOps setups
• 3+ years of experience with AI/ML, intelligent automation (RPA, IDP, workflow automation), advanced analytics or data-drivenproducts including experience taking AI/ML products from concept to production
• Proven experience managing complex product ecosystems, not single applications
• Strong understanding of Finance processes (e.g. Accounting, Reporting, Planning, Compliance) or equivalent experience working closely with Finance organizations

Preferred:

• Proven ability to lead through influence across organizational boundaries
• Strong strategic thinking and decision‑making skills in ambiguous environments
• Ability to quantify and communicate business value, including risk reduction and efficiency gains
• Experience working in large, global, highly regulated environments
• Excellent communication skills across technical and non‑technical audiences
• Experience with Design Thinking, user-centered design & user analysis
• Experience in building product vision, product roadmap, product strategy, and competitive analysis