Forward Deploy AI Engineer — Judgment Labs

davidjoseph-co; San Francisco (CA); On-site; USD 200,000 - 300,000; Full time

Benefits offered by this job

Full benefits

Equinox membership

Private chef

Job summary

davidjoseph-co in San Francisco is looking for a Forward Deploy AI Engineer. You will embed AI systems into customers' workflows and ensure effective integration and monitoring. Ideal candidates have 3–7 years of software engineering experience and strong communication skills.

The role features a generous compensation package of $200,000 to $300,000 plus equity. You'll be part of a dynamic, well-funded team, leading customer engagements in an innovative AI environment.

Qualifications

• 3–7 years of software engineering experience with product-engineering ability.
• Comfort deploying AI or LLM-based systems into production environments.
• Ability to explain complex technical concepts clearly.

Responsibilities

• Deploy and embed the ABM platform into customer systems.
• Guide customers through technical decisions around monitoring and evaluation.
• Translate customer feedback into roadmap input.

Skills

Software engineering

AI experience

Customer-facing communication

Job description

Judgment Labs — Forward Deploy AI Engineer

Type: Full-time | On-site | San Francisco, CA

Compensation: $200,000–$300,000 + 0.1%–0.2% equity

Visa sponsorship: H-1B, O-1, OPT (case-by-case for truly exceptional candidates; main scope is candidates who don't require sponsorship)

About Judgment Labs

Judgment Labs builds infrastructure for Agent Behavior Monitoring (ABM). Where traditional observability focuses on logging exceptions and latency, ABM surfaces behavioral anomalies — instruction drift, context retrieval loss, hallucinations — in scaled production environments. Hundreds of teams building autonomous agents rely on Judgment to understand how their systems behave post-deployment, turning real usage data into scoring and feedback loops that continuously improve agent reliability, performance, and decision‑making at scale.

Founded: N/A | Team size: under 20 | Total funding: $30M+ across two rounds in the past five months | Industry: AI infrastructure / observability / agent tooling | Website: judgmentlabs.ai | Office: San Francisco

Investors: Lightspeed, SV Angel, Valor Equity Partners, Nova Global, Chris Manning, Michael Ovitz, Michael Abbott, Cory Levy, Kevin Hartz. The team ships at 50+ company velocity — Olympiad medalists, debate champions, and competitive athletes; everyone is either an ex‑founder or a founder‑to‑be.

Why Join

• Founder training ground: The scope, judgment, and autonomy required mirror what it takes to found or lead a technical company — own customer engagements end to end across real production systems.
• Deep technical + customer ownership at a fast, well‑funded team: $30M+ raised in five months, top‑tier backers, ships at 50+ company velocity with a sub‑20‑person team.
• Top‑of‑band compensation and perks: $200K–$300K (exceptional AI‑savvy FDE leads up to $400K case‑by‑case), 0.1%–0.2% equity, full benefits, Equinox membership, private chef, direct influence on the product roadmap.

The Role

A Forward‑Deployed AI Engineer who embeds the ABM platform directly into customers’ production systems — integrating monitoring and evaluation into real agent workflows, diagnosing failures in live environments, and driving deployments to reliable production use. Heavily customer‑facing: strong communication is as critical as engineering depth. The team is explicitly prioritizing strong software engineers who can flex into a forward‑deployed role over candidates with a purely solutions / forward‑deployed background.

What You’ll Be Doing

• Deploy and embed the ABM platform and AI components directly into customer codebases and production AI systems.
• Work inside customer systems to integrate monitoring, evaluation, and agent‑facing components into real workflows.
• Guide customers through technical decisions around agent monitoring, evaluation strategy, and integration into existing production systems.
• Own multiple customer engagements end‑to‑end, ensuring successful integration and sustained adoption.
• Translate customer feedback into roadmap input that shapes the next set of features.

Tech stack: Full‑stack with backend/infra weight; production AI / LLM‑based systems.

Requirements

• 3–7 years of software engineering experience, with strong product‑engineering ability that ships features end to end inside customer codebases.
• Some form of applied AI experience (a hard agent requirement and preferred evals requirement are no longer mandatory; a strong engineer with AI‑adjacent exposure is preferred over a pure solutions hire).
• Strong customer‑facing communication skills: explains complex technical concepts clearly, builds trust with technical and non‑technical stakeholders.
• Comfort deploying AI or LLM‑based systems into real production environments.
• Ability to translate ambiguous customer goals into concrete technical solutions.
• The Forward‑Deployed Engineer role is their genuine first choice, not a fallback for another role.
• Based in SF or willing to relocate; 5 days in person.
• Wants to be a technical founder in the future.

Green Flags

• Strong software engineering background from a solid product company (e.g. Roblox, Snapchat, Tesla; Databricks‑tier a bonus).
• Experience deploying AI or LLM‑based systems to production.
• Background from infrastructure/observability companies (e.g. Databricks, Datadog, Cognition).
• 4–5+ years of engineering experience (stronger performance and comms); strong juniors still welcome case‑by‑case.
• Genuinely set on the FDE role as their first choice.
• Technical background (e.g. coding competitions, research experience) in addition to solutions experience.

Red Flags

• FDE is a fallback, not their top choice ("if I can't get X, I'll do FDE").
• Big‑tech candidates using FDE as a backup while angling for another role.
• Pure FDE/solutions background without real software engineering depth (strong on paper but below the technical bar).
• Failed founder who built the exact product but lacks the prestige/pedigree bar (adds noise and variance).
• Low commitment signals: slow to book or drops off before the interview.
• Over‑indexed on agent experience at the expense of engineering quality.

Role Details

Salary: $200,000–$300,000 (Junior/3 yrs: $200K; Mid‑senior/3–7 yrs: up to $300K; exceptional AI‑savvy FDE leads: up to $400K case‑by‑case). Equity: 0.1%–0.2%.

On‑site policy: In‑person San Francisco, 5 days in person (Monday–Friday).

Visa sponsorship: H-1B, O-1, OPT; case‑by‑case for exceptional candidates, main scope is no‑sponsorship.

Employment type: Full‑time. Location: San Francisco, CA.