Product Manager - Data Engine

About the role

Data Engine powers the data workflows behind Applied Intuition's autonomy programs across Cars, Trucks, Industrials, and Defense. We are hiring a Senior Product Manager to make it a coherent platform that technical teams can discover, adopt, and rely on—from bringing data into the system to producing useful, traceable datasets.

Your first customers are the engineers and researchers building autonomy inside Applied. You will work directly with them to understand how they get work done, identify where shared capabilities can replace duplicated effort, and turn their needs into a clear product strategy. Your responsibility extends across ingestion, processing, data discovery, enrichment, quality, and dataset delivery—not just the boundaries of a single engineering team.

You will also own the external product roadmap, customer discovery, and packaging for this platform, working with commercial partners on pricing and go-to-market. You will determine what transfers to external customers and what additional deployment, onboarding, and support capabilities they need.

Success is helping teams complete important workflows more easily, reuse capabilities across programs, and depend less on bespoke integrations and engineering assistance.

At Applied Intuition, you will

• Own the end-to-end product. Set the vision, roadmap, and priorities across multiple teams behind our Data Engine. Define the workflows we support, their users, and what a reliable production experience requires.

• Stay close to users. Observe real workflows, interview users and non-users, investigate workarounds, and combine that evidence with usage and support signals. Make sure teams understand what happened to their feedback and why.

• Build shared capabilities without erasing real differences. Decide what belongs in the common platform, what needs configuration or extension points, and what should remain program-specific. Make explicit choices about what not to build.

• Own adoption beyond launch. Partner with design and engineering on APIs, interfaces, documentation, examples, onboarding, and migrations. Help users find existing capabilities and retire duplicated implementations when the shared path is ready.

• Make technical tradeoffs with engineering. Translate user needs into clear requirements and acceptance criteria. Balance reliability, data quality, latency, cost, compatibility, and delivery speed while respecting security and data-residency constraints.

• Connect internal and external needs. Lead external discovery, define a repeatable offering and its limits, and build a commercial roadmap with sales and customer-facing partners. Avoid turning individual customer requests into permanent product forks.

• Measure outcomes and communicate decisions. Track workflow success, onboarding time, adoption, support effort, and reuse. Explain priorities, tradeoffs, and risks clearly to program teams and leadership.

We're looking for someone who has

• MS/BS in Computer Science, Electrical Engineering, or equivalent experience

• 4+ years of Product Management experience at a top tech company or high-growth startup

• A record of owning complex technical products from discovery through delivery, adoption, and iteration, with senior-level responsibility for decisions and results.

• Experience serving technical users through a shared platform, developer product, or data/ML product, including reconciling competing needs across multiple teams or customers.

• Strong discovery skills: you can distinguish a requested feature from the underlying problem and show how user evidence changed a product decision.

• Sound platform judgment: you can balance reuse with necessary specialization, set support boundaries, and sequence migration without blocking users' work.

• Technical fluency in data flows, APIs, workflow orchestration, data quality, and production operations. You can discuss architectural tradeoffs with engineers.

Nice to have

• Experience with autonomy, robotics, sensor data, or other physical AI workflows.

• Experience with ingestion, catalogs and lineage, data processing, ML data pipelines, or workflow orchestration.

• Experience converting an internal platform into an external product, or supporting customer-controlled and multi-region deployments.

• Prior software engineering experience or hands-on work with technical users, APIs, and developer tooling.