Founding Full-Stack Engineer

Clera; San Francisco (CA); On-site; USD 180,000 - 230,000; Full time

Benefits offered by this job

Early-stage equity

Competitive salary

Job summary

Clera, a leading B2B SaaS startup in AI-powered sales automation, is seeking a Founding Engineer to join their core team in San Francisco. The successful candidate will tackle full-stack problems from LLM orchestration to frontend UI development. You will have a key role in shaping the technical culture and deliver impactful solutions across various platforms.

This role is fully on-site in San Francisco, and candidates must have proven experience in developing conversational agents and Python backend systems.

Qualifications

• Experience designing and building LLM-based conversational agents.
• Production backend development experience in Python.
• Frontend experience with React for building adaptive UIs.

Responsibilities

• Own problems across the full stack from orchestration to front-end widgets.
• Debug conversation logs and improve agent orchestration.
• Prototype generative UI widgets based on sketches within tight deadlines.

Skills

LLM-based conversational agents design

Production backend development in Python

Frontend experience with React

Full-stack feature delivery

Evaluation pipelines and CI/CD workflows

Cloud platforms deployment (AWS/GCP)

Strong written and verbal communication

Tools

Docker

Kubernetes

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:

• 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.

• Experience deploying and operating production services on cloud platforms (AWS or GCP) with Docker; Kubernetes or similar orchestration a plus.

• Strong product sense: ability to rapidly prototype, iterate on feedback, and prioritize high-impact work in a fast-moving environment.

• Experience at an early-stage startup or demonstrated ability to thrive in ambiguous, high-velocity environments.

• Strong written and verbal communication skills — comfortable debugging issues with customers and documenting design decisions clearly.

• Willingness to be available for urgent production issues and participate in on-call or incident response rotations.

Nice to Have:

• Familiarity with reinforcement learning workflows (RL, RLHF, reward modeling) or experimentation frameworks applied to agent improvement.

Compensation & Benefits

• Salary: $180,000 – $230,000 USD annually

• Early-stage equity commensurate with founding engineer role

• Visa sponsorship is not available — candidates must be legally authorized to work in the United States

Location

This role is fully on-site in San Francisco, CA, five days per week. Remote or hybrid arrangements are not available for this position.