Software Engineer, Agent Platform
- Location
- Brooklyn, NY
- Work type
- Full Time · On-site
- Posted
- 2026-10-06
Job description
The opportunity
We're looking for a Software Engineer to build the agent platform that powers materials discovery, from the AI agents that design and run experiments to the applications scientists and customers use to work with them.
You'll report to the Director of Software Engineering and work closely with the rest of the software engineering team. Your time splits between two kinds of work. The first is our agentic system: the agents that run campaigns and propose experiments, plus the evals and infrastructure that make them reliable in production. The second is shipping features end to end: giving an agent a new capability, evolving the campaign data model in Cortex (our Go backend), and building the screens in Tetra (our customer app) or Sentinel (our lab control panel) where people can review and steer the result.
This is not a research role, but you'll work side by side with materials scientists, roboticists and hardware engineers to turn prototypes into production systems that run in our lab.
What you'll do
Agentic System
Build the agents that design materials discovery campaigns, proposing novel compositions that are made and measured in our lab
Build the tools and workflows behind them, such as scientific literature search, simulations and data analysis in a sandbox
Build the evals that measure our agents, from benchmarks to LLM judges, and hill-climb against them to improve agent quality
Instrument agents with tracing, token and cost accounting, and structured logs so you can debug them in production
Work across model providers and adapt our agents as new models change what they can do
Applications
Build Tetra, our SvelteKit application where customers follow and steer their campaigns
Build Sentinel, our lab control panel
Build how people chat with agents and review their work in both apps
Data Layer
Evolve the Cortex data model for campaigns and experiments: protobuf schemas, MongoDB documents and migrations
Build the pipelines that ingest and process scientific documents for our agents
Ship each feature across every layer it touches: the data model, the agent, the API and the UI
Across the stack
Write automated tests and evals on both sides of the API and contribute to CI/CD pipelines
Required qualifications
Core agent and backend expertise
At least 5 years of professional experience building production backend systems
Hands-on experience building and operating LLM-based agents or workflows in production: tool calling, structured outputs, context management, streaming and handling model failures
Understanding of agentic design patterns, such as designer-critic loops and multi-agent systems
Experience measuring agent quality with evals, test sets or LLM judges, and using the results to decide what to change
Frontend, backend and data fundamentals
Professional experience with TypeScript and a modern frontend framework (Svelte/SvelteKit preferred; React or Vue acceptable if eager to learn Svelte), enough to ship a product feature on your own
Experience designing and evolving API contracts (gRPC and Protocol Buffers preferred; REST or GraphQL acceptable)
Working knowledge of databases, data modeling and running production data migrations (MongoDB or document stores preferred)
Comfortable in a polyglot monorepo: our agents are in Python, Cortex is in Go, and our applications are in TypeScript
Communication and collaboration
Clear, precise communicator, especially when working across disciplines
Comfortable operating without a hard boundary between agent, backend and UI: you pick up whichever layer the feature needs, and you know when to pull in a specialist
We actively use AI-assisted development and expect engineers to find their own productive workflows with these tools
Pluses
Experience with agent frameworks, durable execution and LLM observability tools, such as LangChain, Restate, Temporal or Langfuse
Passion for agentic coding tools and keeping up with how fast the field changes
Background in materials science, chemistry or physics
Early-stage startup experience
What we offer
Work closely with a team on the cutting edge of AI research
A mission: an opportunity to fundamentally change the way humanity makes progress through materials science discovery
Compensation
Equal opportunity
Radical AI is committed to equal employment opportunities regardless of race, color, ancestry, national origin, religion, sex, age, sexual orientation, gender identity and expression, marital status, disability, or veteran status.