Founding Forward Deployed Engineer, Harvey
$165-200k
Offers equity and bonus
More information about location
3 days a week in office
Domain-specific AI for legal and professional services
Open for applications
Domain-specific AI for legal and professional services
501-1000 employees
Open for applications
$165-200k
Offers equity and bonus
More information about location
3 days a week in office
501-1000 employees
Company mission
To help professionals develop expertise, faster.
Role
Who you are
- 2+ years building and operating production software with meaningful 0→1 ownership and the ability to operate under ambiguity
- Experience building LLM‑powered applications (retrieval, tools/agents, structured outputs, prompt/runtime safety) and taking them to production
- Comfort working directly with customers—from scoping ambiguous problems to shipping, integrating, training, and iterating on adoption
- Practical experience with evals (designing task suites, pipelines, and dashboards that reflect user quality); you use evals to drive model/product decisions
- Clear, concise communication; low‑ego collaboration; appetite for in‑person pairing with teammates and customers in NYC
- High Beta: You understand that volatility is the normal course of action, and you embrace it. You assume failure is the most likely outcome, so you fail fast and learn. You are transparent about failure, and you actively try to kill your own ideas by tackling the hardest problems first. You don’t subscribe to sunk costs
- Unreasonable hospitality: You practice unreasonable hospitality, grounding your technical work in a deep obsession with the customer. You will spend as much time understanding the "why" from users as you do building the "what," ensuring our bets are aimed at solving real, meaningful problems
- Action, action, and still more action: You live by a relentless bias for action. You believe progress is measured by what you build and learn, not what you discuss in meetings. You prioritize shipping and getting real-world feedback over perfecting a plan on paper
- Contrarian, with common sense: You constantly think about what’s missing, not what’s working well today. You feel uncomfortable when an idea becomes consensus. But you match ambitious ideas with pragmatic execution. You find the most straightforward path to de-risk a complex concept, focusing on proving value quickly rather than over-engineering a solution
What the job involves
- You will be joining as a founding member of Harvey’s Forward Deployed Engineering (FDE) function, helping shape the charter, workflows, and long-term direction of the team
- As an FDE, you’ll embed with Harvey’s enterprise customers (Am Law firms, in-house teams at large enterprises, and other professional services organizations) to turn cutting-edge AI systems into production-ready workflows that deliver measurable outcomes fast
- You’ll move quickly from prototype to deployment, surface patterns from the field, and feed them directly into Harvey’s platform and product roadmap
- Starting from open-ended, high-leverage problems, you’ll design and implement end-to-end solutions with real users and data, shipping under tight feedback loops
- Embed with customers to map out workflows, de‑risk constraints, and define crisp success metrics for custom builds
- Design → prototype → productionize custom workflows: customize knowledge sources and retrieval pipelines, tool use/agents, prompts, and guardrails; then harden them for reliability, observability, and scale
- Integrate workflows with clients systems (DMS, KM, ticketing, identity/SSO) and data sources; standing up secure connectors to the rest of the Harvey platform
- Build and maintain evals & harnesses that capture real‑world quality on a client-by-client basis, wiring those signals into iteration loops and model choices
- Operationalize adoption: run training, write crisp runbooks, and hand-off durable playbooks to customer champions—and to Harvey product/eng—so wins scale beyond one account
- Surface field patterns (recurring prompts, tools, workflows, failure modes) that inform platform capabilities and future product bets
Our take
The explosive popularity of generative AI tools has seen specialized solutions popping up for all kinds of industries. Hoping to help supercharge efficiency and productivity for legal teams, Harvey supplies generative AI that can assist with documentation, as well as aid research and optimize workflows.
Via natural language instructions, Harvey helps draft and analyze legal documents. It can also answer complex questions across large document sets, or even handle research queries that cover multiple domains in legal, regulatory and tax.
Its ability to support legal practitioners as if it's another member of the team is what makes Harvey particularly interesting. This approach has seen the company raise substantial funding, reaching Unicorn status in 2024. Funds are now being used to expand to new geographies, grow headcount and further collect and curate data to train more “domain-specific” AI models.
Kirsty
Company Specialist at Welcome to the Jungle
Company
Funding (last 2 of 9 rounds)
Oct 2025
$160m
LATE VC
Oct 2025
$59m
GROWTH EQUITY VC
Total funding: $1.0bn
Company HQ
Financial District, San Francisco, CA
Leadership
Winston Weinberg
(Co-Founder & CEO)Graduated with a Juris Doctor from the USC Gould School of Law, then spent 1 year as an Associate at O'Melveny & Myers before founding Harvey.
Gabe Pereyra
(Co-Founder & President)Previously worked as a Research Scientist at Meta and DeepMind. Also spent a year as a Brain Resident at Google.
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