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Salary: USD 272,000 - 355,000 / annual
Harvey is an AI platform transforming legal and professional services by combining frontier agentic AI, enterprise-grade infrastructure, and deep domain expertise. The company has strong product-market fit, world-class investor backing, and is scaling rapidly.
You will lead the Backend Platform team, responsible for the shared foundations that enable all product engineering at Harvey. This team owns the frameworks, libraries, and core abstractions used across the organization—from database access and caching to request handling, observability, and context propagation. Your decisions compound across the entire engineering organization.
Key responsibilities include:
- Lead and grow the Backend Platform team through hiring, coaching, and retention of exceptional engineers. Provide clear ownership, meaningful technical challenges, and growth opportunities.
- Define the platform's technical vision and roadmap by partnering with product engineering teams to understand their hardest problems and identify high-impact investments.
- Build the next generation of Harvey's backend foundations, guiding design of shared frameworks for database access, session management, caching, request handling, and streaming with clear interfaces and strong defaults.
- Scale Harvey's architecture by working with Infrastructure to evolve how applications use databases, replicas, and new storage systems, making these capabilities accessible without requiring each product team to solve the same problems independently.
- Build a data access layer enabling entities to move to new stores (KV, NoSQL) without product changes. Make read replicas usable and move high-volume data off the primary.
- Embed reliability into the platform through load testing, circuit breakers, standard outbound clients with timeouts and retries, and noisy-neighbor isolation to prevent cascading failures.
- Make security and reliability properties of the platform by partnering with Security and product teams on safe customer data handling, workspace isolation, and safeguards preventing recurring failure patterns.
- Shape a codebase that both humans and AI can build in confidently by establishing modular boundaries, enforceable contracts, and automated checks.
- Turn platform improvements into customer impact by reducing latency, improving observability, and making production issues easier to diagnose. Measure success through adoption, developer productivity, and product performance.
- Stay close to engineering by leading architecture discussions, reviewing critical code, prototyping when useful, and helping engineers navigate difficult tradeoffs. Partner closely with Infrastructure, Developer Platform, Model Infrastructure, Security, and product engineering leaders.
Requirements:
- 10+ years of software engineering experience and 3+ years of engineering management experience with a track record of building strong teams and delivering complex backend or platform systems.
- Deep technical judgment in backend architecture and distributed systems, including database access patterns, concurrency, caching, API design, and performance.
- Experience building shared libraries, frameworks, or internal platforms adopted by multiple engineering teams, with ability to balance useful abstractions with necessary flexibility.
- Technical depth to engage directly in design and code reviews, investigate difficult systems problems, and guide migrations across large, evolving codebases. Experience with Python and frameworks such as Flask or FastAPI is valuable.
- Track record of hiring, coaching, and developing engineers, setting clear expectations, and creating a culture of ownership and thoughtful execution.
- Strong product instincts for developer tools. Ability to listen closely to engineers, understand where they lose time, and turn feedback into simpler, more effective ways to build.
- Experience embedding reliability, observability, and security into shared systems with measurable improvements in production.
- Clear communication and ability to lead across team boundaries, align people on technical tradeoffs, and drive changes from design through rollout.
- Serious, hands-on use of AI coding agents and opinions on what makes a codebase safe for them to work in.
About Harvey
Legal / Compliance / Risk; AI / Data / Infrastructure — AI platform for legal and professional services work.
