Top Tech Jobs & Startup Jobs in NYC, NY

Own renewals, expansions, retention, and adoption across a high-volume enterprise account portfolio. Lead scaled customer engagements, QBRs, value reviews, and enablement sessions; monitor customer health and adoption data to identify churn risks; advise customers on integrating AI solutions into workflows; and collaborate with Sales, Product, and Legal Engineering on customer insights, roadmap influence, and scalable success processes.

Build and ship secure, high-performance software for AI-powered legal and professional-services systems. Responsibilities span frontend, backend, full-stack, infrastructure, and applied AI work, including retrieval, document intelligence, workflow automation, LLM evaluation, enterprise agents, and secure client-data systems. Collaborate with AI Research, Legal Engineering, Product, Design, and experienced engineers through design discussions and code reviews while contributing production code from the start.

Own US employee relations matters from intake through resolution, including performance concerns, conduct issues, investigations, conflict resolution, and sensitive separations. Partner with managers, People Business Partners, and Employment Legal to guide decisions, conduct impartial investigations, manage employee communications, and resolve cases fairly. Build case-management practices, manager resources, training, and data-informed improvements while maintaining confidentiality and supporting a fast-growing technology company.

Delivers customized Harvey platform training to attorneys and legal departments, supports customer onboarding, expansion, and renewals, and creates scalable educational content. Partners with Sales, Customer Success, Product, and Engineering to understand client goals, gather feedback, and improve the product. The role requires legal expertise, practical experience building AI agents and workflows for legal use cases, strong communication, and comfort with frequent customer interactions.

Support a VP in a fast-paced environment by managing complex calendars, multi-destination travel itineraries, meeting preparation, communications, presentations, and follow-up. The Executive Assistant will coordinate with internal teams, customers, partners, and external stakeholders; protect confidentiality; support team culture and morale; and independently drive ad hoc projects to completion.

Partners with Customer Success, Legal Engineering, and adjacent GTM teams to shape strategy, improve processes, establish operating cadences, and drive high-impact cross-functional initiatives. Translates stakeholder insights into recommendations on priorities, resourcing, and execution while aligning Sales, RevOps, Finance, Product, and overlay organizations around shared goals.

Manage relationships with major enterprise customers, lead Harvey AI implementation and adoption, monitor account health, deliver training, engage executives, advocate for customer needs, and provide product feedback. The role requires strategic planning, change management, stakeholder influence, and up to 25% travel. Candidates should have management consulting, technology advisory, enterprise SaaS customer success, account management, or legal industry experience.

Lead Harvey’s content design practice across product interfaces and AI responses. Define voice, tone, terminology, interaction patterns, and content principles; design key experiences from concept through execution; and create AI-assisted tools and guidance that scale content quality. Partner with product designers, engineers, PMs, and AI researchers to establish systems, communicate tradeoffs, and bring clarity to ambiguous problems while maintaining a high standard for writing and user experience.

Own the content strategy and execution for Harvey’s global events, including agenda curation, speaker recruitment and preparation, session design, and the Product Keynote. Manage event workstreams, timelines, trackers, rehearsals, and cross-functional coordination across Product, Marketing, Creative, Production, and Leadership. Build speaker relationships, analyze post-event feedback, and ensure programming supports strategic goals and delivers a high-quality attendee experience.

Build synthetic data pipelines, evaluation systems, benchmarks, verifiers, rubrics, and quality metrics for legal AI models and agentic workflows. Partner with researchers and legal experts to translate domain judgment into measurable training signals, investigate model failures, ensure data quality and provenance, and connect customer feedback to improved evaluations and training data.