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# Full-Stack Engineer

- **Company:** David Joseph & Company
- **Location:** San Francisco, CA, United States
- **Experience:** Experienced
- **Salary:** $200,000.0 - $300,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Operational Databases, Large Language Models, Backend, Data Layers
- **Published:** August 9, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=ff0bcb6576eb5ca6

## About the Role

* 3-7 years of full-stack engineering experience, comfortable owning systems from the data layer through the UI
 * Hands-on experience building with LLMs or AI agents (or a clear, demonstrated drive to ramp fast)
 * A track record of shipping and scaling production systems end to end
 * Comfortable working directly with customers to understand needs and solve real problems (~30% of the role)
 * Strong problem-solving in fast-moving, ambiguous environments
 * Clear, direct, persuasive communication across technical and non-technical audiences
 * Based in San Francisco or open to relocating; in-office 5 days a week, * Prior work on evals, observability, or agent behavior-monitoring products
 * Strong engineering pedigree from a respected product company; top-tier infrastructure experience is a bonus
 * Prior forward-deployed or solutions engineering experience
 * Early-stage / 0-to-1 startup experience as an early hire
 * A technical edge beyond delivery - coding competitions, research, or similar
 * Founder background or a clear founder-to-be trajectory
 * Full-stack comfort with real backend and infrastructure depth

## Description

This is a genuine full-ownership product-engineering role, not spec implementation. You'll talk to customers, decide what to build, build it, and iterate until it's great - across the entire stack, from the data layer to the UI. Expect to work on agent-investigation interfaces, verification and evaluation platforms, and a developer SDK. About 30% of the role is customer-facing.

What you'll be doing

 * Build interfaces that make large-scale, parallel agent investigations legible - turning thousands of production traces and a wide range of failure signals into a single actionable answer.
 * Build the platform for verifying agent changes: simulated environments for stateful evals, trajectory replay, and monitors for unintended behavior.
 * Make long, multi-step reasoning trajectories understandable in minutes.
 * Own the improvement loop end to end, turning production data into datasets, judges, and regression checks.
 * Build and maintain the SDK and a terminal-first developer experience.
 * Own core platform infrastructure: workspaces, permissions, billing, usage, and limits.

Tech stack: Full-stack (data layer through UI), SDK development, terminal-first tooling, agent/LLM infrastructure.


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