Role Overview:

The role suits someone who has moved from software engineering into product management and enjoys building AI-first enterprise products. You will work closely with Product, Engineering, AI/ML teams, patent domain experts and business stakeholders to turn customer needs into scalable product capabilities for patent and IP professionals across the US and Europe.

This is a hands-on role that needs real technical depth, product thinking and execution focus. Because the products generate legal work product, correctness is not negotiable: 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.

What you will do:

- Work with Product Leadership, Engineering, business stakeholders, customers and subject-matter experts to shape product roadmaps and turn strategic priorities into executable product plans.

- Conduct customer discovery, market research and competitive analysis to identify and size product opportunities.

- Translate customer needs into clear product requirements, and prioritise initiatives by customer value, business impact and technical feasibility.

- Drive product features through the full lifecycle, from discovery and requirements through launch and continuous improvement.

- Define detailed product requirements, user stories, acceptance criteria and measurable success metrics.

- Work with AI and engineering teams building products with LLMs, retrieval-augmented generation (RAG), agentic workflows, document intelligence and automation.

- Help 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 behaviour is measured, monitored and continuously improved.

- Work closely with patent subject-matter experts and QA teams to validate AI-generated outputs.

- Translate expert feedback into structured product requirements, evaluation datasets, test scenarios and continuous product improvements.

- Help build robust validation processes that ensure enterprise-grade quality and trust in AI-generated outputs.

- Partner closely with software engineers, AI engineers, architects, UX teams and Product Leadership throughout the product development lifecycle.

- Take part confidently in technical discussions about APIs, system architecture, AI workflows, data pipelines and implementation decisions.

- Translate complex customer and business problems into well-defined engineering requirements and product specifications.

- Support sprint planning, backlog refinement, release planning and Agile ceremonies.

- Proactively identify risks, dependencies and delivery roadblocks.

- Partner with Product Leadership and customer-facing teams to understand enterprise customer workflows and evolving business needs.

- Monitor market trends, emerging AI technologies and competitor offerings to find new product opportunities.

- Track adoption, customer satisfaction, usage metrics and business outcomes to drive continuous improvement.

- Collaborate across Product, Engineering, AI/ML, Design, QA, business units and domain experts to deliver successfully.

- Communicate product priorities, feature progress, trade-offs and outcomes clearly to stakeholders.

Qualifications & experience:

- A bachelor's degree in Computer Science or Computer Engineering (B.Tech./B.E.) from a reputed institution is mandatory. Candidates should have started their careers as software developers or engineers before moving into product management.

- 3 - 6 years of overall experience, including product management, with a prior foundation in software engineering.

- Experience building or managing AI/ML-powered SaaS products in a product company or AI-first startup serving international customers.

- Demonstrated experience working closely with engineering teams to deliver technically sophisticated software. The ability to understand software architecture, APIs, AI workflows and technical trade-offs is essential.

- Strong understanding of modern AI: large language models, retrieval-augmented generation, AI agents, prompt engineering, evaluation frameworks and AI guardrails.

- Experience building products for enterprise customers in North America and/or Europe is strongly preferred.

- Proven experience in B2B SaaS product organisations.

- Has taken one or more products or major product capabilities from concept through successful release.

- Domain knowledge in legal tech, intellectual property, enterprise workflow automation, document intelligence or knowledge management is an advantage.

Technical competencies:

- Comfortable in detailed technical discussions with engineering, making informed product decisions on architecture and implementation trade-offs.

- Strong understanding of AI product development: LLMs, RAG, AI agents, prompt engineering, evaluation methodologies, AI guardrails and human-in-the-loop validation.

- Experience with Jira, Confluence, Figma, Productboard (or equivalent), SQL, analytics platforms and Agile product development.

- Able to write detailed user stories, acceptance criteria, product specifications and release plans with real technical depth.

Behavioural competencies:

- Curious, hands-on and intellectually rigorous, with a genuine passion for technology, AI and hard customer problems.

- Excellent analytical and structured problem-solving, with the ability to simplify complex technical and business challenges.

- Strong communication and stakeholder management across Product, Engineering, AI/ML, Design, Sales, QA and domain experts.

- Comfortable with ambiguity, making data-informed decisions and iterating quickly on customer feedback and product learnings.

Skills:

- Product Management, AI Products, LLMs, RAG, AI Agents, AI Evaluation, Guardrails, Human-in-the-loop, B2B SaaS, Product Roadmap, User Stories, Agile, Jira, Confluence, Figma, SQL, Document Intelligence, LegalTech.