Company
SaaS
FoundingFullStackEngineer
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Founding Full Stack Engineer. Skills: LLM orchestration, Full stack development, Conversational agents. Own problems across the full stack. Debug conversation logs”
Industry & Context.
Debug issues; Troubleshooting
On-call rotation, Urgent production issues
What They're Looking For.
Must Have
Proven experience designing and building LLM-based conversational agents, Production backend development experience in Python, Frontend experience with React, Demonstrated ability to deliver full-stack features end-to-end, Experience building evaluation pipelines, automated regression tests, observability tooling, and CI/CD workflows, Experience designing deployment and versioning infrastructure for agents, Experience with voice-enabled or browser-based agents, Product sense, Experience at an early-stage startup, Written and verbal communication skills, Willingness to be available for urgent production issues
Nice to Have
Experience deploying and operating production services on cloud platforms with Kubernetes or similar orchestration a plus
What You'll Do.
Own problems across the full stack
Debug conversation logs
Prototype generative UI widgets
Trace quality regressions
Design agent versioning infrastructure
How You'll Work.
Team & Collaboration
Core member of a tiny team; Set technical culture
Communication Scope
Written communication; Verbal communication; Document design decisions
Full Job Description
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:
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