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Afternoon Regression Jobs (NOW HIRING)

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 ...

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 ...

QA Engineer

OR · On-site +1

... regression testing, and final release sign-off. * You'll partner closely with Product Managers ... Are available in the afternoons - we prioritize everyone's personal time and work-life fit, but ...

... regression throughout the permanency process. The Permanency Clinician will work in conjunction ... The position is primarily Monday through Friday with afternoons/evenings comprising most of the ...

... regression throughout the permanency process. The Permanency Clinician will work in conjunction ... The position is primarily Monday through Friday with afternoons/evenings comprising most of the ...

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How much do afternoon regression jobs pay per hour?

As of Sep 1, 2026, the average hourly pay for afternoon regression in the United States is $51.44, according to ZipRecruiter salary data. Most workers in this role earn between $42.55 and $59.38 per hour, depending on experience, location, and employer.

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States with the most job openings for Afternoon Regression jobs include:

Founding Full Stack Engineer

San Francisco, CA • On-site

Clera
1 - 10 employees

$180K - $230K/yr

Full-time

Re-posted 10 days ago


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.