Product Intelligence Engineer

About the role

ABOUT MATTER INTELLIGENCE

Welcome to Matter, where we are building the future of vision AI: pairing a world-first sensor that sees molecular chemistry, temperature, and 3D shape with a Large World Model that will be the most powerful intelligence engine for the physical world. This system doesn't just see what something looks like; it understands everything from a single pixel. We call this Superintelligent Vision.

Our team has delivered technologies to Mars for NASA/JPL, designed advanced sensors for U.S. Defense, and frontier artificial intelligence systems. We are now building the next generation of space- and airborne-based sensing systems.

ABOUT THE ROLE

Matter is hiring a Product Intelligence Engineer to turn physics-informed models, general-purpose AI, and ultraspectral data into secure, evidence-backed intelligence products. Reporting to Ignacio Cases Martin, this hands-on individual contributor will build agentic workflows, retrieval and tool integrations, reports, and human-in-the-loop experiences that help customers make operational decisions.

KEY RESPONSIBILITIES

- Build production workflows that combine physics-informed models, LLMs, VLMs, world models, scientific code, data services, and deterministic rules through stable interfaces.

- Design durable execution across state, planning, model routing, retrieval, memory, tool use, retries, timeouts, checkpoints, human approval, and recovery.

- Create evidence-backed outputs that distinguish source data, model inference, system-generated synthesis, user input, and unresolved uncertainty.

- Partner with product and design to build workflows for review, correction, comparison, approval, reporting, and recovery.

- Build context, retrieval, memory, and indexing patterns that respect permissions, freshness, versioning, retention, and evidence lineage.

- Evaluate real system behavior across task success, groundedness, scientific validity, safety, latency, cost, and human intervention.

QUALIFICATIONS

REQUIRED

- Experience building production AI applications, agent systems, workflow engines, backend services, or complex software products.

- Strong hands-on engineering skills across APIs, stateful services, databases, asynchronous execution, testing, debugging, and production operation.

- Practical experience with LLMs or multimodal systems, retrieval, memory, tool use, model routing, structured generation, and common failure modes.

- Product judgment and the ability to connect technical design choices to the user decision or workflow being improved.

- Experience building systems with security, permissions, data isolation, auditability, or human-approval requirements.

PREFERRED

- Experience with scientific, geospatial, industrial, defense, autonomy, or other high-consequence intelligence systems.

- Experience building multimodal applications that combine imagery, maps, time series, documents, structured data, or sensor streams.