Agent Infrastructure (IC)
About The Position
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 built core infrastructure at OpenAI. We are now building the next generation of space- and airborne-based sensing systems. About the Role Matter is hiring an Agent Infrastructure Engineer to build the production systems that turn physics-informed and general-purpose AI into secure, evidence-backed intelligence and action. Reporting to Ignacio Cases Martin, this hands-on individual contributor will work across agent runtimes, reasoning graphs, model routing, retrieval, memory, tools, durable execution, and human approval in partnership with research, platform, product, design, and evaluation teams.
Requirements
- Required 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 Haves
- 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.
Responsibilities
- Build and operate a production agent runtime that composes physics-informed models, LLMs, VLMs, world models, scientific code, data services, and deterministic business rules through stable interfaces.
- 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 without one-off orchestration.
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
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
