Why This Job is Featured on The SaaS Jobs
Forward Deployed Engineering has become a distinct pattern in enterprise SaaS, sitting between product engineering and customer delivery to shorten the path from platform capability to measurable adoption. In Harvey’s case, the listing signals a mature enterprise footprint and a platform-led AI product, where field learnings can directly shape how agentic workflows are packaged, secured, and operationalised across many accounts.
For a SaaS career, this role builds uncommon range across the full post-sale lifecycle: discovery, integration, production hardening, and rollout. The emphasis on evals, observability, and reliability reflects how modern AI SaaS differentiates beyond demos, and experience building feedback loops from real usage into roadmap decisions transfers well to platform, solutions architecture, and product-facing engineering paths across the sector.
This is best suited to engineers who like alternating between deep technical implementation and structured stakeholder work, and who are comfortable making progress from ambiguous starting points. It will appeal to professionals who want proximity to enterprise constraints such as identity, data systems, and governance, and who prefer roles where customer context is a first-class input to what gets built.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
Why Harvey
At Harvey, we’re transforming how legal and professional services operate — not incrementally, but end-to-end. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come.
This is a rare chance to help build a generational company at a true inflection point. With 1000+ customers in 58+ countries, strong product-market fit, and world-class investor support, we’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched.
Our team is sharp, motivated, and deeply committed to the mission. We move fast, operate with intensity, and take real ownership of the problems we tackle — from early thinking to long-term outcomes. We stay close to our customers — from leadership to engineers — and work together to solve real problems with urgency and care. If you thrive in ambiguity, push for excellence, and want to help shape the future of work alongside others who raise the bar, we invite you to build with us.
At Harvey, the future of professional services is being written today — and we’re just getting started.
Role Overview
As a senior member of our founding Forward Deployed Engineer (FDE) team, 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‑grade workflows that deliver measurable outcomes fast. You’ll move from prototype to deployment quickly, surface patterns from the field, and feed them back into Harvey’s platform and product roadmap. You’ll start from open‑ended, high‑leverage problems, design and implement end‑to‑end solutions with real users and data, and ship to production under tight feedback loops.
This role is based in New York, NY. We use an in-person work model and offer relocation assistance to new employees..
What You'll Do
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.
How you will make a 10x Impact
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 You Have
5+ 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.
Compensation Range
$200,000-$260,000 USD
#LI-SB1
Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.
We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai
