Group Product Manager, AI & Data

Job Description

Job Description

Overview

Rightsline is building the AI-native platform for IP commerce. We are moving from a modern system of record into an agentic product model. AI Assistants are in the market today, our first line of Agents coming next, and a longer arc that reshapes how our customers do the work of rights, royalties, and finance flows. Underneath the AI product line sits a modern analytics and reporting platform (Snowflake plus Sigma) that every product consumes.

We are hiring a Group Product Manager, AI & Data to lead the execution of that arc. You will personally own and build our AI product line as the working PM – PRDs, prototypes, discovery, and launches shipping on your own hands. Alongside that, you will directly manage Senior Product Manager(s) / Product Manager(s) and grow the AI & Data team as the Group's scope expands. You will set the craft bar for how we discover, build, evaluate, launch, and monetize AI products at Rightsline; make the build-vs-leverage-vs-partner calls across proprietary and third-party AI; and be the person the CPO and Executive Leadership Team look to for whether our AI bets are compounding into shipped customer value.

This is a player-coach product management role with a defined growth path as the Group scales and performs above expectations. The right candidate reads that path as motivating and the builder-first framing as freeing.

Build the AI Product Line – Hands-On

• Personally own our AI product line as the working PM. You are the one running discovery, writing the PRDs, building the prototypes, and shipping new AI products into production. 

• Reimagine workflows in the world of AI: customer-back and future-first. We are not extrapolating today's product with AI sprinkled on. Fundamentally change how the work gets done, then design the surface.

• Solve pain first. Every AI capability starts from a real, named customer job not from what a model can do. If we cannot describe the pain in a customer's own words, we do not build it.

• Best-in-class, modern user experience. The AI surface is where our product feels different. Hold a top-tier UX bar with confidence indicators, human-in-the-loop patterns, exception handling, latency, and trust design as product properties.

• Own the MCP integration surface both how our AI products consume model and tool contexts, and how Rightsline exposes its own capabilities as MCP services for external agents over time.

• Own the AI product vision and multi-quarter roadmap for the Group. Translate the CPO's portfolio strategy into a sequenced, defensible plan and a board-approved agentic product vision.

• Establish evals and telemetry / LLMOps as foundational not optional. Own the accuracy / trust / usability / cost tradeoff and be accountable when we get it wrong.

• Guard the naming bar: functional names, no personas or marketing wrappers.

Cohesive AI Strategy – Proprietary + Third Party Partners

• Own a coherent AI strategy across proprietary Rightsline capabilities and best-in-class third-party AI. The customer sees one product, one experience, one trust model not a patchwork of vendors.

• Make explicit build-vs-leverage-vs-partner calls for every AI capability, and maintain an explicit "will not do" list. 

• Publish and maintain the Group's thesis on where AI creates compounding moats for Rightsline (proprietary data, workflow context, domain models).

Customer Discovery, JTBD & Design Partners

• Run discovery on a Jobs to Be Done frame: map the user's full end-to-end role, not just the 30% that lives inside our product today. The 70% outside our product is the expansion opportunity.

• Structured customer validation before scaling.

• Bring customers along as design partners. Early Access Programs and co-design cadences are how AI capabilities graduate from prototype to GA not internal opinion.

Pricing, Packaging & Monetization

• Own pricing, packaging, and monetization strategy for AI at Rightsline. Reason clearly across the modern set of AI monetization models like bundled features, add-on copilots, standalone AI products, and platform-plus-usage and match the model to the product shape.

• Test pricing like a product launch. Beta cohorts, EAPs, preferential pricing during the pilot, then lock the model. Output-based, credit-based, and hybrid subscription-plus-usage are all on the table depending on the product shape.

• PLG motion where it makes sense. Some AI surfaces may open a product-led entry point into Rightsline. You own identifying and running those bets when the shape fits.

Success Metrics & Financial Attribution

• Own the AI product scorecard end-to-end including active adoption across the customer base, revenue attributed to AI capabilities, and customer value achieved.

• Instrument every AI product for telemetry and LLMOps from day one. Financial attribution including expansion attached to AI, retention impact, ARR uplift as first-class product responsibility.

Manage Product Manager(s)

• Personal build cadence is non-negotiable. PRDs, prototypes, and discovery cycles you personally run are part of the Group’s output – measured and reviewed alongside the ships your direct report(s) own. Personal ship is not optional; it is what makes the coach credible.

• Directly manage a Senior Product Manager on day one. Set the Group’s craft standard: PRD quality, prototype rigor, launch discipline, and eval discipline. Every PM ships PRDs plus user stories plus working prototypes. 

• Build out the AI & Data PM team over time. As the AI product line matures and demands more PM coverage, you will hire additional PMs into the Group. Sequencing and shape are yours to propose to the CPO.

Cross-Pillar & GTM Partnership

• AI is horizontal. Partner with Rights & Platform and Royalties & Financials PMs to embed Assistants and Agents where they compound the most. Never build in isolation, never let AI become a silo.

• Work hand-in-glove with Engineering leadership on architecture, model selection, LLM-vs-deterministic tradeoffs, and integration surface area. Earn the room in technical discussions.

• Partner with the CRO, Marketing, and Client Expansion on positioning, packaging, and landing AI capabilities. Sign off on Group launch claims for accuracy and defensibility.

• 7–10 years of Product Management experience in B2B enterprise SaaS. Direct management experience is a plus but not the primary bar; the primary bar is having personally built and shipped AI products. Prior direct management of ICs is required as this seat manages a Senior Product Manager on day one. The primary weight in evaluation, however, sits on having personally built and shipped AI-native products; direct management experience alone, without shipped AI product, does not clear the bar.

• Proven track record shipping AI-native products to production not AI features bolted onto existing workflows. You have personally taken at least one Agent-class product from zero to shipped, adopted, and measured.

• Fluency with modern LLM application patterns including MCP servers, evals, prompt design, RAG, human-in-the-loop workflows, cost curve management, model selection, and telemetry / LLMOps. 

• Direct hands-on use of Claude, Codex, Cursor, or comparable AI development tooling in your own daily workflow.