{"schemaVersion":"jobsearcher.job.v1","id":"7fd9a5e79dbd94271b236f3b","url":"https://jobsearcher.com/jobs/7fd9a5e79dbd94271b236f3b","canonicalUrl":"https://jobsearcher.com/jobs/7fd9a5e79dbd94271b236f3b","title":"Software Engineer, Agent Platform","description":"Compensation $165,000 – $295,000 · per year · USD\r\nThe opportunityWe'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.\r\nYou'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.\r\nThis 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.\r\nWhat you'll doAgentic SystemBuild the agents that design materials discovery campaigns, proposing novel compositions that are made and measured in our lab\r\nBuild the tools and workflows behind them, such as scientific literature search, simulations and data analysis in a sandbox\r\nBuild the evals that measure our agents, from benchmarks to LLM judges, and hill-climb against them to improve agent quality\r\nInstrument agents with tracing, token and cost accounting, and structured logs so you can debug them in production\r\nWork across model providers and adapt our agents as new models change what they can do\r\nApplicationsBuild Tetra, our SvelteKit application where customers follow and steer their campaigns\r\nBuild how people chat with agents and review their work in both apps\r\nData LayerEvolve the Cortex data model for campaigns and experiments: protobuf schemas, MongoDB documents and migrations\r\nBuild the pipelines that ingest and process scientific documents for our agents\r\nShip each feature across every layer it touches: the data model, the agent, the API and the UI\r\nAcross the stackWrite automated tests and evals on both sides of the API and contribute to CI/CD pipelines\r\nRequired qualificationsCore agent and backend expertiseAt least 5 years of professional experience building production backend systems\r\nHands-on experience building and operating LLM-based agents or workflows in production: tool calling, structured outputs, context management, streaming and handling model failures\r\nUnderstanding of agentic design patterns, such as designer-critic loops and multi-agent systems\r\nExperience measuring agent quality with evals, test sets or LLM judges, and using the results to decide what to change\r\nFrontend, backend and data fundamentalsProfessional 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\r\nExperience designing and evolving API contracts (gRPC and Protocol Buffers preferred; REST or GraphQL acceptable)\r\nWorking knowledge of databases, data modeling and running production data migrations (MongoDB or document stores preferred)\r\nComfortable in a polyglot monorepo: our agents are in Python, Cortex is in Go, and our applications are in TypeScript\r\nCommunication and collaborationClear, precise communicator, especially when working across disciplines\r\nComfortable 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\r\nWe actively use AI-assisted development and expect engineers to find their own productive workflows with these tools\r\nPlusesExperience with agent frameworks, durable execution and LLM observability tools, such as LangChain, Restate, Temporal or Langfuse\r\nPassion for agentic coding tools and keeping up with how fast the field changes\r\nBackground in materials science, chemistry or physics\r\nEarly-stage startup experience\r\nWhat we offerWork closely with a team on the cutting edge of AI research\r\nA mission: an opportunity to fundamentally change the way humanity makes progress through materials science discovery\r\nCompensationThe base salary range for this role is $165,000–$295,000. Where an offer lands depends on experience, skills, and scope.\r\nEqual opportunityRadical 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.#J-18808-Ljbffr","company":"Nodi","rawCompany":"nodi","city":"New York","state":"NY","isRemote":false,"isActive":true,"createdAt":"2026-10-10T01:22:51.706Z","occupations":[{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1251.00","title":"Computer Programmers","slug":"computer-programmers"}],"industries":[{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Software Engineer, Agent Platform","description":"Compensation $165,000 – $295,000 · per year · USD\r\nThe opportunityWe'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.\r\nYou'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.\r\nThis 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.\r\nWhat you'll doAgentic SystemBuild the agents that design materials discovery campaigns, proposing novel compositions that are made and measured in our lab\r\nBuild the tools and workflows behind them, such as scientific literature search, simulations and data analysis in a sandbox\r\nBuild the evals that measure our agents, from benchmarks to LLM judges, and hill-climb against them to improve agent quality\r\nInstrument agents with tracing, token and cost accounting, and structured logs so you can debug them in production\r\nWork across model providers and adapt our agents as new models change what they can do\r\nApplicationsBuild Tetra, our SvelteKit application where customers follow and steer their campaigns\r\nBuild how people chat with agents and review their work in both apps\r\nData LayerEvolve the Cortex data model for campaigns and experiments: protobuf schemas, MongoDB documents and migrations\r\nBuild the pipelines that ingest and process scientific documents for our agents\r\nShip each feature across every layer it touches: the data model, the agent, the API and the UI\r\nAcross the stackWrite automated tests and evals on both sides of the API and contribute to CI/CD pipelines\r\nRequired qualificationsCore agent and backend expertiseAt least 5 years of professional experience building production backend systems\r\nHands-on experience building and operating LLM-based agents or workflows in production: tool calling, structured outputs, context management, streaming and handling model failures\r\nUnderstanding of agentic design patterns, such as designer-critic loops and multi-agent systems\r\nExperience measuring agent quality with evals, test sets or LLM judges, and using the results to decide what to change\r\nFrontend, backend and data fundamentalsProfessional 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\r\nExperience designing and evolving API contracts (gRPC and Protocol Buffers preferred; REST or GraphQL acceptable)\r\nWorking knowledge of databases, data modeling and running production data migrations (MongoDB or document stores preferred)\r\nComfortable in a polyglot monorepo: our agents are in Python, Cortex is in Go, and our applications are in TypeScript\r\nCommunication and collaborationClear, precise communicator, especially when working across disciplines\r\nComfortable 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\r\nWe actively use AI-assisted development and expect engineers to find their own productive workflows with these tools\r\nPlusesExperience with agent frameworks, durable execution and LLM observability tools, such as LangChain, Restate, Temporal or Langfuse\r\nPassion for agentic coding tools and keeping up with how fast the field changes\r\nBackground in materials science, chemistry or physics\r\nEarly-stage startup experience\r\nWhat we offerWork closely with a team on the cutting edge of AI research\r\nA mission: an opportunity to fundamentally change the way humanity makes progress through materials science discovery\r\nCompensationThe base salary range for this role is $165,000–$295,000. Where an offer lands depends on experience, skills, and scope.\r\nEqual opportunityRadical 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.#J-18808-Ljbffr","datePosted":"2026-10-10T01:22:51.706Z","dateModified":"2026-10-10T01:22:51.706Z","hiringOrganization":{"@type":"Organization","name":"Nodi","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"New York","addressRegion":"NY","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"7fd9a5e79dbd94271b236f3b"},"url":"https://jobsearcher.com/jobs/7fd9a5e79dbd94271b236f3b"}}