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San Francisco, California, United States
Onsite
Samba TV is a media intelligence company. We use consented, large-scale viewership and consumer data to help the biggest brands in the world make smarter decisions about how they reach and understand their audiences.
We're building a new AI-powered product with a real-time, conversational interface. Users interact with a system that researches, reasons, and produces real deliverables — interactive charts and data views, structured outputs, and downloadable documents — as it works. It's a modern, AI-native, type-safe codebase, and the hard problems involve long-running agentic sessions in front of enterprise customers, where latency, cost, and graceful failure decide whether the product feels trustworthy.
We're looking for a Full Stack Engineer to join our Agentic Product Engineering team in San Francisco. This is a genuinely full-stack role that spans the whole request path: an AI/agent backend, the Node/TypeScript service layer that fronts it, and the React streaming UI on top. You'll own meaningful pieces of it end to end and grow your range across the rest. You'll also be someone the team can rely on to carry front-end work when it needs coverage, but the front end is one facet of the job, not its center.
Build across the whole system. Work end to end across the AI/backend engine, the service layer, and the UI. Own the features you ship — how they stream, how state is modeled, how they fail — and contribute to the broader design conversations about orchestration boundaries, streaming protocols, the type-safe client-to-server contract, artifact and file-delivery flows, and persistence.
Build on the backend and AI layer. Work in the engine that powers the product — extending backend services and their capabilities, wiring model interactions and structured outputs, handling streaming, and managing state and persistence. Reason about latency, cost, and failure modes as you go.
Work in the service layer. Extend the Node backend-for-frontend between the UI and core services — building endpoints, streaming responses (SSE) to the browser, enforcing auth, and keeping the client-to-server contract type-safe end to end.
Ship UI, and provide front-end coverage. Build a streaming, chat-style interface in React on a modern SSR framework — live token streams, progress indicators, and inline interactive content — and turn structured data into interactive charts, tables, and the download/preview experience for generated documents (e.g., PPTX, PDF).
Get streaming and async right. Handle the realities of long-running, asynchronous work end to end: partial/streaming state, loading and "generating" transitions, reconnection, large-payload handling, and graceful behavior when a request fails mid-flight.
Raise quality. Write unit, integration, and end-to-end tests, instrument what you ship on both the client and the server, and use logs, traces, and error tracking to debug issues that span the UI and the services behind it.
Help get real launches out the door. We ship on a staged progression with real users at every step. You'll be part of that: shipping into live cohorts, watching how the product behaves, and fixing what the staging surfaces before it reaches the next group.
Understand the context you're working in. Build a working model of how the system and its downstream dependencies behave, and use it to make good implementation calls on well-scoped work rather than waiting for fully-specced tickets.
Collaborate. Partner with product, design, and platform/backend engineers, and communicate clearly in code review, design discussion, and technical writing.
A full-stack engineer with real range. You've owned significant features end to end across the stack — services, APIs, and UI. You default to action, but you also think about the second-order effects of a design.
Strong in JavaScript/TypeScript and Node. This is the center of the role. You write clean, type-safe code and lean on the type system rather than fight it, and you're comfortable working in backend services and APIs and reasoning about data flowing over REST and SSE.
Genuinely full-stack, with real front-end depth where it counts. You have meaningful, hands-on React experience and a solid grasp of the web platform. What matters most here isn't breadth of UI work — it's judgment on the hard parts: streaming and asynchronous state (SSE, WebSockets), reconnection and mid-flight failure, rendering performance under long-running token streams, and accessibility. You can reach for AI tools to move fast, but you own the correctness of what ships rather than trusting generated code to get these edge cases right. You can carry front-end work when the team needs coverage, without needing it to be the bulk of your work.
A clear thinker about trade-offs. You can weigh options, write up a design clearly, and explain the "why" so others can build on it and push back on it.
Fundamentals. Solid with relational databases (PostgreSQL) and SQL, Git, and CI/CD. You understand how applications get deployed to the cloud (AWS, GCP, or Azure) and how to operate what you ship.
A good collaborator. You explain technical ideas clearly, give constructive review, and are open to feedback. You disagree well.
Education / experience. A Bachelor's degree in Computer Science, Computer Engineering, or a related technical field, or equivalent practical experience. Typically 4+ years of professional full stack / web application development.
Experience with a modern SSR/full-stack React framework (Next.js, Remix, or TanStack Start) and the surrounding ecosystem (Query, Form, Router).
Familiarity with AI / LLM application development — streaming chat UIs, tool-calling, or agentic/multi-agent patterns. Exposure here is a strong plus.
Familiarity with type-safe API contracts (tRPC, Hono RPC, or GraphQL) shared across a monorepo.
Comfort with modern tooling: pnpm monorepos, Vite, and a TypeScript-first workflow.
Experience with auth flows (Auth0, OAuth/OIDC, JWTs) in a single-page or SSR app.
Familiarity with observability tooling — Sentry, OpenTelemetry, Prometheus/Grafana, or similar — for debugging and operating production systems.
Experience in AdTech, MediaTech, or data-heavy product environments.
Knowledge of scripting (Python, Go, or shell) for automation and testing.
