Agent Infrastructure (IC)

The role

This individual contributor will build production systems that turn physics-informed and general-purpose AI into secure, evidence-backed intelligence and action. The role involves working across agent runtimes, reasoning graphs, model routing, retrieval, memory, tools, durable execution, and human approval.

What you will do

• Build and operate a production agent runtime that composes models, LLMs, VLMs, world models, scientific code, data services, and deterministic business rules.
• Design durable execution with state, planning, tool selection, retries, timeouts, cancellation, checkpoints, provenance, human approval, and recovery.
• Build retrieval, RAG, memory, and indexing patterns that respect tenancy, permissions, freshness, versioning, retention, and evidence lineage.
• Create evidence-first outputs that distinguish source data, model inference, system-generated synthesis, user input, and unresolved uncertainty.
• Integrate continuous evaluation across task success, groundedness, scientific validity, safety, latency, cost, and human intervention.
• Partner with product, design, AI platform, Signal and Evaluation, and Telemetry teams to create reusable APIs, tools, and human-in-the-loop workflows.

Required qualifications

• Experience building production agent infrastructure, applied-AI platforms, workflow engines, distributed systems, or complex AI products.
• Strong hands-on software engineering skills across architecture, APIs, stateful services, databases, asynchronous execution, testing, debugging, and production operations.
• Practical experience with LLMs, VLMs, multimodal systems, RAG, memory, tool use, model routing, structured generation, and common agent failure modes.
• Experience building systems with security, permissions, data isolation, auditability, and human approval requirements.
• Sound product judgment and the ability to explain uncertain system behavior precisely across technical and non-technical teams.

Nice to have

• Experience with scientific, geospatial, industrial, defense, autonomy, or other high-consequence customer-intelligence systems.
• Experience building multimodal applications that combine imagery, time series, maps, documents, structured data, or sensor streams.
• Experience with agent evaluation, reinforcement learning or world-model environments, model routing, constrained decoding, or durable workflow systems.
• Familiarity with edge or intermittently connected operation, local model execution, or mixed cloud and edge architectures.

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

Before you apply

• Applicants must be a U.S. citizen or national, a lawful permanent resident (green card holder), or eligible to obtain required authorizations from the U.S. Department of State to comply with U.S. expo

About the company

Matter is building the future of vision AI by pairing a sensor that sees molecular chemistry, temperature, and 3D shape with a Large World Model. The team has delivered technologies to Mars for NASA/JPL and designed advanced sensors for U.S. Defense.