---
title: 'Member of Technical Staff, Deployment Engineer at Judgment Labs'
canonical: 'https://feeny.ai/job/member-of-technical-staff-deployment-engineer-judgment-labs-san-francisco-ranv5hk3awje'
type: 'job'
last_seen: '2026-11-12'
---

# Member of Technical Staff, Deployment Engineer at Judgment Labs

- **Company:** Judgment Labs
- **Location:** San Francisco, CA
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-10-20
- **Last confirmed live:** 2026-11-12
- **Apply:** https://jobs.ashbyhq.com/judgmentlabs/d6613cd7-9b73-4ebb-85be-d6aa0584f1ee

## Job description

## About Judgment

Judgment Labs is building the infrastructure for continual learning in long-horizon AI agents. We turn long agent trajectories into clean, structured data for evals, labeling, rubric generation, context engineering, and RL workflows. Instead of only showing teams what happened, Judgment helps decide what matters, what should be learned from, and how that learning should flow back into the agent. We’ve raised $32M across two rounds led by Lightspeed.

## The Role

You'll own the end-to-end customer process, from understanding their pain points, to building their evals and monitoring in Judgment, to turning what you learn into what we build next. This role centers on deep technical execution, customer ownership, and product judgment. You will work directly with customer teams to reason about agent behavior and translate high-level goals into concrete ABM deployments. You'll partner with our AEs before customers sign and stay with them after. Then you'll take what you learn across customers and turn it into product direction: deciding what's worth building, prototyping it, and demoing it. You'll ship PRs and prototypes, but your main job isn't owning large systems end to end. It's making sure we build the right things. The scope, judgment, and autonomy required in this role mirror a training ground for what it takes to found or lead a technical company.

## What You’ll Do

- Partner with AEs on technical sales: run discovery and demos, answer product questions, and show prospects how Judgment fits their agents.
- Deploy and embed Judgment Labs' ABM platform and AI components into customer codebases and production AI systems, integrating monitoring and evaluation into real workflows.
- Guide customers through technical decisions around agent monitoring, evaluation strategy, and integrating these capabilities into existing production systems.
- Own multiple customer engagements end-to-end, from the first technical conversation through successful integration and sustained adoption, in Slack and on calls.
- Turn feedback across customers into product direction: what to build, what to fix, and what not to build.
- Prototype and demo new features with coding agents, ship PRs when it makes sense, and work with engineering to get the right changes shipped.

## What We’re Looking For

You identify with at least one of the following:

- Experience deploying AI or LLM-based systems into real production environments.
- Ability to quickly learn new tools and systems, and integrate AI infrastructure into existing customer workflows and codebases.
- Ability to translate ambiguous customer goals into concrete technical solutions and evaluation strategies.
- Strong product sense: you can hear what a customer asks for, find the problem underneath, and explain clearly what's worth building.
- Comfort prototyping and shipping changes quickly with coding agents.
- Strong customer-facing skills, including explaining complex technical concepts clearly and building trust with both technical and non-technical stakeholders.
- Comfort owning customer engagements end-to-end, from the first call through successful production adoption.
- You want to be a technical founder in the future.

Why Judgment?

- Agents can’t work without this: Today’s agents hallucinate, drift, and break in production. We’re building the infrastructure that fixes this: the monitoring layer that makes agents self-improving.
- We’re wired to win: We're a team of 20 but we ship like 50+ on the daily. You'll be working with olympiad medalists, debate champions, and competitive athletes who bring that same intensity to company building.
- Fast track to founding: Our engineers interface directly with customers, ship code into their environments, and use their feedback to dictate what’s next on the roadmap. Everyone on the team is either an ex-founder or a founder-to-be.
- We make sure our people do their best work: If you deserve a spot on the team, money will never get in the way of it. Full benefits, Equinox, and a private chef to take care of you. We sprint hard but we play hard, ask us about our Smash/Mario Kart tournaments.

We work in person in San Francisco, Monday–Friday.

## About Judgment Labs

## Company Overview
- **One-liner**: Judgment Labs builds a continuous-improvement stack for AI agents, helping teams monitor, evaluate, and improve agent behavior in production.
- **Entity Type**: Private (Seed + Series A funded)
- **Headquarters**: San Francisco, California, United States
- **Founded**: 2025
- **Founders**: Alex Shan (CEO), Andrew Li (Chief Scientist), Joseph Camyre (CTO)

## Core Business
- **Primary industry**: AI Infrastructure / Agent Observability
- **Target customers**: B2B — AI-native companies and engineering teams building and deploying autonomous AI agents
- **Mission or purpose**: Provide the infrastructure for a future where billions of AI agents act autonomously, giving teams the tools to make their products better with every interaction.

## Products & Services
- **Behavior Discovery**: Automatically constructs and refines evaluation rubrics from verifiable signals, surfacing failure modes and usage patterns from unlabeled production trajectories.
- **AutoRubrics**: Automates the creation of evaluation criteria for agent behavior.
- **Agent Search**: Enables querying across agent trajectories at a behavioral level, beyond simple input/output keyword search.
- **Agent Judge**: Builds cheaper and more accurate trajectory-level evaluators using harnesses.
- **Slack & MCP Integrations**: Allows teams to investigate issues, run tests, and take action directly from Slack, Claude, Codex, Cursor, or any MCP client.

## Market Standing
- **Valuation/Market Cap**: Not disclosed
- **Key Metric**: $32M in total funding (Seed + Series A, announced May 2026)
- **Notable Investors/Partners**: Lightspeed Venture Partners (led both rounds), Nova Global, SV Angel, Valor Equity Partners, Dynamic. Key partner: James Alcorn (Partner at Lightspeed) sits on the board.
- **Growth Signals**: +400% YoY headcount growth (19 employees as of mid-2026); platform already in production at a growing list of agent-native companies; company describes customer traction as “extraordinary.”

## Competitive Advantages
- First-mover advantage in a new category: agent behavior monitoring (ABM) infrastructure, built specifically for deep, multi-step agent trajectories rather than simple chatbot input/output evals.
- Founders have deep domain expertise: CEO Alex Shan was an AI researcher at Stanford’s NLP group under Chris Manning; Chief Scientist Andrew Li was an early research hire at TogetherAI; CTO Joseph Camyre built large-scale infrastructure at Datadog.
- Product is already standardizing within agent-native startups, creating a network effect as more production data flows through the platform.

## Strategic Focus
- Aggressively hiring AI researchers and engineers in San Francisco.
- Expanding the forward-deployed engineering team to serve a growing customer base.
- Mission: “Give every team building agents the tools to make their products better with every interaction.”

## Why Work Here
- **Culture**: Described as fast-moving, high-agency, and intellectually ambitious — values critical thinking, questioning assumptions, and taking bold bets.
- **Work Policy**: On-site in San Francisco (all roles require physical presence at HQ).
- **Notable Perks**: Work at the frontier of AI agent infrastructure; join a small but rapidly growing team (19 people) backed by top-tier VCs; early employees will define the company’s trajectory and culture.
- **Engineering Culture**: Emphasis on research engineering, rapid prototyping, and productionizing cutting-edge AI evaluation methods.

## Sources
1. [judgmentlabs.ai](https://judgmentlabs.ai/)
2. [judgmentlabs.ai/careers](https://www.judgmentlabs.ai/careers)
3. [linkedin.com/company/judgmentlabs](https://www.linkedin.com/company/judgmentlabs)
4. [builtin.com](https://builtin.com/company/judgment-labs)
5. [businesswire.com](https://www.businesswire.com/news/home/20260512621556/en/Judgment-Labs-Closes-%2432M-in-Seed-and-Series-A-Funding-to-Build-the-Continuous-Improvement-Layer-for-AI-Agents)

## Other roles at Judgment Labs

- [Founding Business Development Representative](https://feeny.ai/job/founding-business-development-representative-judgment-labs-san-francisco-3qpghh46cqhz) — San Francisco, CA
- [Member of Technical Staff, Agents](https://feeny.ai/job/member-of-technical-staff-agents-judgment-labs-san-francisco-t4ryveqq2yns) — San Francisco, CA