Product Manager - Formulation AI Platform

The Formulation AI Platform PM is responsible for building and scaling the platform capabilities that enable activation of new Formulation AI product families. In this mid-level role, you will drive the delivery of a scalable, reusable platform - coordinating enhancements across engineering, data science, and business teams - while translating technical capabilities into measurable business value for leadership and stakeholders across the chemicals and manufacturing organization.

You will operate in a complex, cross-functional environment with a high degree of ambiguity, balancing technical depth with strategic communication and prioritization.

Key Responsibilities

1. Activation Strategy & Delivery

• Partner with Activation PM's to define the endtoend activation strategy, roadmap, and OKRs for the Formulation Platform, covering awareness, onboarding, enablement, and expansion.
• Shape platform requirements based on deep understanding of user goals, operational constraints, and input from MVP and Activation teams.
• Translate business needs from R&D, manufacturing, and technical teams and into platform requirements, user stories, and backlog items.
• Evaluate feature requests and manage tradeoffs between scalability, time-to-value, and technical feasibility in a fast-moving development environment.
• Accept completed work, review increments, and guide user experience considerations that impact activation success

2. Platform Scalability & Adoption Enablement

• Design and evolve platform enablement programs - including onboarding guides, playbooks, and internal champion networks - to drive adoption of new Formulation AI capabilities.
• Identify process changes required to embed AI-driven formulation workflows into daily R&D and manufacturing operations.

3. CrossFunctional Collaboration & Technical Alignment

• Lead cross-functional teams including data scientists, ML engineers, IT, domain experts, and business stakeholders through the full product development lifecycle.
• Facilitate design sessions, requirement workshops, and architecture reviews to align teams on platform goals, dependencies, and constraints.
• Partner with activation PMs and product owners across formulation domains to ensure platform capabilities are usable, well-documented, and production-ready.
• Serve as a bridge between technical teams and business stakeholders, ensuring alignment on priorities and visibility into delivery progress.
• Provide content and key decisions for steering meetings as part of the functional AI operating model

4. Data, Telemetry & Integration Awareness

• Establish and monitor platform health metrics, adoption funnels, and usage analytics to inform prioritization and continuous improvement.
• Develop a strong understanding of underlying data dependencies, integrations, and infrastructure (cloud, data pipelines, ML model serving) relevant to formulation AI execution.

5. Financials, Partner Management & Operating Model

• Build business cases and value assessments tied to platform capabilities and new product family activation.
• Support development and refinement of the operating model for scaling Formulation AI use cases across business units and geographies.
• Manage partner SOWs for external vendors, prototyping engagements, or AI framework integrations as needed.

Qualifications

• Bachelor's degree in a technical or business field.
• 3+ years in product management, data science, or AI/ML product roles.
• Strong experience with AI/MLbased product development, usercentered design, and MVPdriven iteration cycles.
• Proven experience leading activation, onboarding, or adoption programs for digital or AI products.
• Experience communicating complex technical concepts to a variety of audiences with both technical and nontechnical audiences.
• Understanding of distributed systems, cloud computing (AWS, Azure, Databricks preferred), and software development life cycle
• Willingness to travel 30-40%.

Preferred

• Advanced degree (MBA, MS, PhD) in engineering, computer science, datarelated fields, or a scientific discipline.
• Background in platform product management, API product strategy, or developer-facing products.
• Familiarity with MLOps, data engineering, or AI/ML model lifecycle management.
• Experience building or scaling AI adoption programs within large, matrixed organizations.
• Experience with Agile, SAFe, or similar delivery methodologies.

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