Judgment Labs — Agent Product Engineer

davidjoseph-co; San Francisco (CA); On-site; USD 200,000 - 350,000; Full time

Benefits offered by this job

Full benefits package

Equity

Private chef

Job summary

Judgment Labs is hiring an Agent Product Engineer to build high‑taste products for self‑learning agents. The role focuses on full‑stack work with a strong emphasis on agent infrastructure and product development, ideal for candidates with front‑end/design engineering or AI engineering backgrounds who have shipped agents in production.

You will translate customer feedback into product iterations, contribute across the stack, and help scale a small team while delivering customer‑facing features

Qualifications

• Engineering experience (3-7 years) required or similar.
• Agent or Applied AI background required.
• 0-1 product ownership comfort.
• Front-end/design engineer or AI engineer background acceptable.
• TypeScript fluency required.
• Evals experience heavily preferred.

Responsibilities

• Build high-taste agent products with strong UX polish.
• Design and ship agent capabilities from 0 to 1 within a fast-scaling product surface.
• Contribute across the full stack, focusing on agent infrastructure and product.
• Translate customer feedback into concrete product iterations.

Skills

Engineering experience

Agent/Applied AI

Product ownership

Front-end/AI engineer

TypeScript

Evals experience

Job description

Judgment Labs — Agent Product Engineer

Type: Full-time | On-site | San Francisco (FiDi), CACompensation: $200,000–$350,000 + Competitive EquityHiring count: 1Visa sponsorship: Yes — H-1BReports to: Not specified on the page

About Judgment Labs

Judgment Labs builds infrastructure for Agent Behavior Monitoring (ABM). Where traditional observability logs exceptions and latency, ABM surfaces behavioral anomalies — instruction drift, context retrieval loss — in production at scale. Hundreds of teams building autonomous agents rely on Judgment to understand post-deployment behavior: clustering patterns across conversations and workflows, correlating regressions to specific interaction types, and pinpointing where reliability breaks down.

Founded: Not stated | Team size: ~19 (per role body) | Total funding: $30M+ (two rounds in the past 5 months)Industry: AI infrastructure / agent observability & evalsWebsite: judgmentlabs.aiOffice: San Francisco (FiDi)Investors: Lightspeed, SV Angel, Valor Equity Partners, Nova Global, Chris Manning, Michael Ovitz, Michael Abbott, Cory Levy, Kevin Hartz, and others.

Why Candidates Should Join

• Funded momentum: $30M+ raised across two rounds in five months from top-tier investors.
• Build 0-to-1: ship agent capabilities from a blank page on a fast-scaling product surface.
• Founding-track: small (~19-person) team; fast track to founding-level experience and direct customer interaction.
• Perks: full benefits package, Equinox membership, private chef.

Intake Call Summary

• No intake call summary was present on the role page. (flag — request from Contrario if one exists.)

The Role

Judgment Labs is hiring an Agent Product Engineer to build high-taste products for self-learning agents. The role is majority agent work on a full-stack baseline. Candidates can come from a front-end/design engineering background or an AI engineering background, but both must have prior experience building and designing agents, ideally at a startup with 0-1 product ownership.

What You’ll Be Doing

• Build high-taste agent products that pair powerful behavior with consumer-grade UX polish
• Design and ship agent capabilities from 0 to 1 inside a fast-scaling product surface
• Contribute across the full stack as needed, with the majority of work on agent infrastructure and product
• Translate customer feedback on agent behavior into concrete product iterations
• Help raise the bar on product taste and craft as the team grows past 19 people

Tech stack: TypeScript (full-stack); no further stack specified.

Requirements

• 3-7 years engineering
• Agent or Applied AI background required
• 0-1 product ownership comfort
• Front-end/design engineer or AI engineer
• TypeScript fluency
• Evals experience heavily preferred

Green Flags

• Shipped agents in production at a startup. Can walk through context design, tool design, reasoning loop tradeoffs.
• Strong product engineering range. Has shipped customer-facing product features end to end, not just backend infrastructure or research artifacts.
• Demonstrably strong communicator. Customer calls, internal demos, technical writing, public talks, or comparable signal of comfort explaining complex AI concepts.
• Prior evals, observability, or behavior-monitoring product experience. Direct adjacency to Judgment's space, heavily preferred.
• Prior 0-1 product ownership at a seed or Series A startup. Built agents from a blank page.
• High-intensity background signal: olympiad medals, debate competitions, competitive athletics, founder experience, or comparable high-output indicators.

Red Flags

• No prior agent or Applied AI experience. The bar is production agent work.
• Front-end or design engineering only without agent depth.
• Backend or infrastructure only without product-shipping experience or customer-facing range.
• Weak customer-facing skills. The seat is customer-facing, candidates who want heads-down only are not the fit.
• Traditional ML or model-training background without agent system experience.
• Cannot or will not work 5 days in person at the FiDi office.

Role Details

Salary$200,000–$350,000EquityCompetitive (not quantified)On-site policy5 days/week in office (Monday–Friday), FiDiVisa sponsorshipH-1BEmployment typeFull-timeLocationSan Francisco (FiDi), CA (header shows "Chinatown, CA" — see flag)

Screening Questions

(Contrario "Required Candidate Q&A" form fields)

1. Where are you currently located?
2. LinkedIn URL
3. Are you legally authorized to work in the United States?
4. Will you require work sponsorship now and/or in the future?
5. Are you located in the San Francisco-area and/or willing to relocate?
6. Are you willing to work on-site in our San Francisco office Monday-Friday?

Interview Process

Stage 1 — Pending Approval — Candidates awaiting initial approval.Stage 2 — Founder vibe check (30 min) — Plus optional 15‑min deeper dive into technical projects.Stage 3 — Technical Interview (75 min) — Problem-solving (30 min) + role-specific interview (45 min).Stage 4 — Work TrialStage 5 — Offer ExtendedStage 6 — Candidate Hired — When the candidate accepts and starts.

Ideal Companies & Backgrounds

Pulled from the role page's Ideal Companies grid.

Clearly recognizable: Linear, Cursor, Ramp, Figma, Vercel, CockroachDB, Modal Labs, Anyscale, Runway, Applied Intuition, Anduril, Notion, Nomic AI, MotherDuck, LangChain

Ideal Candidate Profiles

None provided on the role page.

Rejected Candidate Feedback

None provided on the role page.