Technical Product Manager

We are looking for a highly Technical Product Manager to own product capability across the platform. This role suits someone who has moved from software engineering into product management and wants to build AI-first enterprise products. You will work closely with engineering and AI teams and with IP domain experts, turning real user needs into scalable product capability for patent and IP professionals in the US and Europe. It is a hands-on role requiring confidence in technical discussions on architecture, APIs, and AI workflows, and the ability to make informed trade-offs. Because the products generate legal work product, correctness is critical. You will help define product requirements, validation approaches, and quality measures for AI systems where accuracy, explainability, and expert validation matter as much as innovation.

Responsibilities:

• Shape product roadmaps with product leadership, engineering, customers, and subject matter experts, and turn strategic priorities into executable plans.
• Run customer discovery, market research, and competitive analysis to identify and size opportunities.
• Translate customer needs into clear requirements and prioritize based on customer value, business impact, and technical feasibility.
• Drive features through the full lifecycle, from discovery and requirements through launch and continuous improvement.
• Define detailed requirements, user stories, acceptance criteria, and measurable success metrics.
• Work with AI and engineering teams building on LLMs, retrieval-augmented generation, agentic workflows, document intelligence, and automation.
• Define evaluation criteria, quality benchmarks, guardrails, human-in-the-loop validation, and acceptable failure modes for AI-powered features.
• Partner with engineering on evaluation frameworks and quality metrics so model behavior is measured, monitored, and continuously improved.
• Work with patent subject matter experts and QA to validate AI-generated outputs and turn expert feedback into structured requirements, evaluation datasets, and test scenarios.
• Build validation processes that give enterprise customers grounds to trust AI-generated output.
• Partner closely with software engineers, AI engineers, architects, and UX and product leadership across the development lifecycle.
• Participate confidently in technical discussions covering APIs, system architecture, AI workflows, data pipelines, and implementation decisions.
• Translate complex customer and business problems into well-defined engineering requirements and specifications.
• Support sprint planning, backlog refinement, and release planning, and surface risks, dependencies, and blockers early.
• Work with product leadership and customer-facing teams to understand enterprise customer workflows and evolving needs.
• Track market movement, emerging AI capabilities, and competitor offerings to identify new opportunities.
• Monitor adoption, satisfaction, usage metrics, and business outcomes, and act on what they show.
• Communicate priorities, progress, trade-offs, and outcomes clearly across product, engineering, AI and ML, design, QA, and domain teams.

Requirements:

• Six to ten years of overall experience, including product management, with a prior foundation in software engineering.
• Bachelor's or master's degree in computer science or engineering from a reputed institution.
• Experience building or managing AI- and ML-powered SaaS products in a product company or AI-first startup.
• Proven record of working closely with engineering teams to deliver technically sophisticated software, with the ability to understand architecture, APIs, AI workflows, and technical trade-offs.
• Strong grasp of modern AI technologies, including large language models, retrieval-augmented generation, AI agents, prompt engineering, evaluation frameworks, and guardrails.
• Experience taking at least one product or major capability from concept through launch and beyond for a B2B SaaS product for enterprise customers in North America or Europe is strongly preferred.
• Comfortable in detailed technical discussions with engineers and able to make informed product decisions involving architecture and implementation trade-offs.
• Strong understanding of AI product development, including LLMs, RAG, AI agents, prompt engineering, evaluation methodology, guardrails, and human-in-the-loop validation.
• Ability to write detailed user stories, acceptance criteria, specifications, and release plans with real technical depth.
• Working knowledge of Jira, Confluence, Figma, Productboard, or equivalent, plus SQL, analytics platforms, and Agile practices.
• Curious, hands-on, and intellectually rigorous, with genuine interest in technology, AI, and hard customer problems.
• Analytical and structured, able to simplify complex technical and business challenges.
• Strong communicator across product, engineering, AI and ML, design, sales, QA, and domain experts.
• Comfortable with ambiguity, making data-informed decisions and iterating quickly on customer feedback.

Nice To Have:

• Domain knowledge in legal technology, intellectual property, enterprise workflow automation, document intelligence, or knowledge management platforms.
• Startup experience and comfort operating in an early-stage environment with a strong sense of ownership.