Product Intelligence Engineer

Matter Intelligence • San Francisco, CA

6d • Onsite

About The Position

Matter is hiring a Product Intelligence Engineer to turn physics-informed models, general-purpose AI, and ultraspectral data into secure, evidence-backed intelligence products. 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.

Requirements

• 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.

Nice To Haves

• 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.
• Experience with agent evaluation, constrained generation, program synthesis, durable workflow systems, or mixed cloud and edge architectures.
• Experience working closely with product and design teams to ship customer-facing capabilities.

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.

Benefits

• Competitive compensation based on experience
• Early-stage equity package
• 100% employer-paid health, dental, and vision coverage
• Opportunity to work on novel sensing, data, and AI systems with real-world deployment paths to the largest industries in the world

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed