Product Manager, Platform & Integrations

cerebre is on a mission to build the data foundation of the physical world. We offer a live intelligence map of a facilities – built from schematics to power AI. Often called the “brain” of the digital twin, cerebre helps engineers, data scientists, and business teams understand data within the context of the plant. We collaborate with the world’s largest companies and most innovative partners who are transforming the industrial sector. cerebre is a global team of engineers, scientists, innovators, and explorers united by a mission to help the world’s largest manufacturing facilities build and use intelligence. Our development team is made up of world-class engineers who design and deliver novel solutions. This is an opportunity to join a market-leading team that is changing how the industrial world works. We believe flexibility drives creativity and that our team should live and work where we can be our best selves. We’re 100% remote and offer a competitive time-off package to ensure time for rest and recharge.

• 5-8+ years of professional experience in product management, with a track record of owning technical or platform-facing product areas.
• Strong working knowledge of APIs and integration patterns, both exposing data out (APIs, MCP server) and bringing external data sources in.
• Working knowledge of AI and agentic systems, including understanding how LLMs and MCP-style integrations work.
• Comfort operating in highly technical product spaces, partnering closely with engineering on architecture trade-offs.
• Self-starter with sharp instincts for identifying key customer and user needs.
• Strong communication skills, able to translate between engineering, partner-facing, and business stakeholders.
• Experience with Agile methodologies: backlog grooming, sprint planning, and retrospectives.
• Analytical thinking: comfortable using usage data and integration feedback to prioritize development.
• At least C1 English level for effective collaboration in a global team.

Nice to have:

• Previous experience building developer-facing platforms, API products, or SDKs.
• Experience working with or building on MCP, LLM tool-calling, or agentic frameworks.
• Experience with data ingestion, ETL/integration pipelines, or partner/vendor data onboarding.
• Familiarity with graph databases, query languages, or knowledge graph systems.
• Experience running growing and novel product surface areas.
• Familiarity with industrial data, engineering software, or digital twins.
• Background in data-driven product development and analytics.

• Own the consumption layer: Define and drive the roadmap for how engineers, operators, third-party systems, and LLMs access and query PlantGraph, including but not limited to APIs, MCP servers, etc.
• API & integration strategy: Design and prioritize the technical surface area that external systems and AI agents use to consume graph data, balancing flexibility, performance, and ease of integration.
• External data & third-party integrations: Own how external data sources and third-party systems integrate into our product suite (e.g., historian data, other OT systems, partner or vendor platforms), including partnering with customers to define integration patterns, data contracts, and onboarding processes for new sources.
• Partner across the product team: Work closely with the product team, who own core experience and end-user workflows, to make sure the consumption layer supports what users, customers and partners actually need.
• Translate strategy into execution: Turn technical and business requirements into clear specs, API contracts, and acceptance criteria that engineering can build against.
• Sprint Planning & Execution: Partner with engineering to plan sprints, ensure clarity on deliverables, and resolve blockers, particularly around integration and platform dependencies.
• Market & Ecosystem Insights: Track how customers, partners, the broader industry and others outside the industry are inventing novel approaches to data integration, building with LLMs, agentic systems, etc.
• Performance Tracking: Define and monitor KPIs around adoption, reliability, and consumption patterns.
• Customer & Partner Engagement: Support technical conversations with customers and partners