Technical Product Lead - AI Platform

Accountabilities

• • Own the product strategy, roadmap, prioritization, and quarterly objectives for an AI-powered patent intelligence platform, balancing client value, competitive opportunities, engineering feasibility, and available resources.
  • Identify underserved customer segments and develop product opportunities that expand the platform's reach across law firms, corporate IP teams, and other professional users.
  • Define API-first and integration strategies and coordinate product dependencies across full-stack, platform, security, and other technical teams.
  • Design LLM workflows by developing system prompts, tool definitions, structured output specifications, and multi-step agent architectures for complex patent-analysis use cases.
  • Establish evaluation frameworks and rubrics for AI workflows, maintain versioned prompt libraries, and continuously improve outputs using evaluation data, expert feedback, and hallucination analysis.
  • Act as the final quality gate for AI-generated patent intelligence, ensuring outputs meet the professional accuracy standards expected by sophisticated legal and corporate IP users.
  • Build and maintain gold-standard evaluation datasets based on attorney-reviewed ground truth and use them to benchmark and improve AI workflows.
  • Investigate and escalate legal accuracy risks, including fabricated citations, incorrect claim interpretation, scope inflation, and jurisdictional inconsistencies.
  • Work directly with clients and legal professionals to gather feedback, demonstrate new capabilities, manage expectations, and translate real-world needs into product and engineering requirements.
  • Lead an async-first, outcome-oriented delivery model focused on shipping high-value capabilities efficiently, while using automation and AI-generated reporting to reduce unnecessary process overhead.
  • Make technical tradeoff decisions involving accuracy, latency, cost, context windows, caching, model selection, and data freshness.
  • Manage relevant budgets, vendors, AI providers, data providers, and product tooling while maintaining disciplined technical and operational practices.

  Requirements

  • 3–10 years of combined experience across patent-domain work and B2B SaaS product management, with a preference for 5+ years in B2B SaaS product management and at least 2 years in a domain with significant legal or regulatory accuracy requirements.
  • USPTO-registered patent agent status or a JD with substantial patent prosecution or litigation experience.
  • At least 3 years of hands-on experience with claim charts, invalidity contentions, freedom-to-operate analyses, office action responses, or comparable patent-analysis work.
  • Strong knowledge of patent concepts including claim construction, infringement and invalidity analysis, prior art under §§102/103, prosecution history, §112 issues, portfolio strategy, and related IP workflows.
  • Familiarity with patent analytics and research platforms such as Patlytics, Derwent Innovation, Orbit Intelligence, PatSnap, or Google Patents Advanced.
  • Demonstrated experience shipping AI-powered products or features for enterprise legal, IP, or similarly high-accuracy professional environments.
  • Strong understanding of LLM architecture, including context windows, temperature, sampling, prompt engineering, structured outputs, tool/function calling, and hallucination mitigation.
  • Hands-on knowledge of multi-step agent architectures using technologies such as LangGraph or equivalent frameworks.
  • Experience with LLM evaluation methodologies, golden datasets, LLM-as-judge approaches, legal accuracy metrics, and platforms such as Braintrust or equivalent tools.
  • Ability to understand and manage AI cost, latency, scalability, and performance tradeoffs, including prompt caching, token economics, batching, and context management.
  • Comfort working with tools such as Anthropic Claude API, LangSmith, LangGraph, GitHub, JIRA, or comparable technologies.
  • Ability to write precise product and LLM workflow specifications that engineering teams can implement with minimal clarification.
  • Strong client-facing communication skills, including the ability to demonstrate products, handle challenging technical and legal questions, and incorporate expert feedback.
  • Demonstrated ability to operate independently in an async-first environment without relying on a dedicated Scrum Master or QA team.
  • Excellent judgment, prioritization, communication, and stakeholder-management skills, with the confidence to challenge assumptions when necessary.
  • A technical undergraduate degree in engineering, computer science, chemistry, biology, or a related field is preferred.
  • Direct experience collaborating with patent attorneys, major law firms, or in-house intellectual property teams is strongly valued.

  Benefits

  • Compensation: Expected total annual compensation of $135,000–$275,000, potentially including base salary and eligible variable compensation.
  • Compensation may vary based on geographic location, market conditions, patent credentials, AI/LLM production experience, and overall seniority.
  • Health & well-being: Medical, dental, and vision insurance with significant employer contributions toward employee premiums.
  • Retirement: 401(k) program with a competitive employer match.
  • Performance incentives: Variable compensation tied to individual performance and overall organizational success.
  • Time off: Accrued paid time off, company holidays, and additional floating holidays.
  • Wellness: Dedicated wellness leave supporting physical and emotional well-being.
  • Life-event support: Paid leave for parental bonding and bereavement.
  • Work arrangement: Fully remote, flexible work environment designed around autonomy and ownership.
  • Professional growth: Merit-based advancement opportunities, mentorship, professional development, and resources to support career progression.
  • Global collaboration: Opportunity to work with a distributed, multicultural team and collaborate with colleagues and clients across regions.