Founding Full Stack Engineer

About the role

ABOUT THE ROLE

A well-funded, early-stage B2B SaaS startup in the AI-powered sales automation space is hiring its first Founding Engineer. You'll join the CTO as a core member of a tiny, high-caliber team and help set the technical culture for everyone who comes after. The company builds self-improving conversational agents that run product demos 24/7 — adapting to each buyer, handling technical questions, and getting smarter with every conversation. Growth has tripled month-over-month and demand is accelerating.

WHAT YOU'LL WORK ON

There are no strict lanes here. You'll own problems across the full stack, from LLM orchestration to embeddable frontend widgets to eval pipelines. Key technical pillars include:

- The Agent: LLM orchestration, conversation flow, tool use, and voice. Agents must understand unfamiliar products and explain them clearly to prospects with varying levels of context.

- The Experience: Embeddable, generative UI that adapts in real-time — fast-loading, interactive, and responsive across products and screen sizes.

- The Platform: Customer-facing tooling for configuring agents, managing flows, reviewing conversations, and measuring performance.

- Evals & Self-Improvement: Pipelines that measure agent quality and feed learnings back automatically, so demos get smarter without manual intervention.

- Infrastructure: Zero cold starts, instant agent response, and versioning systems that let customers preview changes before they go live.

DAY-TO-DAY EXAMPLES

- Debug conversation logs, trace where an LLM lost the thread during a pricing objection, and ship a fix to the orchestration layer by lunch.

- Prototype a generative UI widget in an afternoon based on a whiteboard sketch and have something demo-able by end of day.

- Trace a quality regression to a prompt change, roll it back, and add an automated test to prevent recurrence.

- Design agent versioning infrastructure from scratch so customers can safely preview updates.

WHAT WE'RE LOOKING FOR

Required:

- Proven experience designing and building LLM-based conversational agents — orchestration, tool use, prompt engineering, and conversation flow.

- Production backend development experience in Python (services, APIs, backend infrastructure).

- Frontend experience with React — building interactive, adaptive UIs and rapid prototyping.

- Demonstrated ability to deliver full-stack features end-to-end: frontend, backend, integration, and deployment.

- Experience building evaluation pipelines, automated regression tests, observability tooling, and CI/CD workflows.

- Experience designing deployment and versioning infrastructure for agents (feature flags, preview environments, versioned rollouts).

- Experience with voice-enabled or browser-based agents (STT/TTS, WebRTC, or browser automation) or equivalent voice/browser + LLM integration experience.