Software Engineer, Agent Platform

Nodi; New York (NY); On-site; USD 165,000 - 295,000; Full time

Job summary

Nodi in New York, NY is seeking a Software Engineer to build the agent platform powering materials discovery. You will design and ship production backends and frontends that run experiments and enable scientists and customers to interact with them.

You’ll work across the agentic system, Cortex Go backend, and Tetra/ Sentinel UIs, collaborating with scientists and hardware engineers to turn prototypes into scalable production systems in our lab.

Qualifications

• At least 5 years of professional experience building production backend systems.
• Hands-on experience with LLM-based agents or workflows in production: tool calling, structured outputs, context management.
• Experience designing API contracts (gRPC and Protocol Buffers preferred).
• Working knowledge of databases and data migrations (MongoDB or document stores preferred).

Responsibilities

• Build the agents that design materials discovery campaigns and proposed experiments.
• Develop tools and workflows for literature search, simulations and data analysis.
• Create evals and benchmarks to measure agent quality.
• Instrument agents with tracing, cost accounting and logs for production debugging.
• Work across model providers and adapt agents as new models change capabilities.
• Ship features across data model, agent, API and UI.

Skills

Backend systems

LLM agents

TypeScript

API design

Communication

Tools

Go

Python

TypeScript

MongoDB

Protobuf

gRPC

Job description

Compensation $165,000 – $295,000 · per year · USD

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 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

The base salary range for this role is $165,000–$295,000. Where an offer lands depends on experience, skills, and scope.

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.