Senior Product Manager - Seller Mastery

Who we are

Mindtickle is the leading AI-powered revenue enablement platform that combines on-the-job learning and deal execution to drive behavior change and get more revenue per rep. Mindtickle is recognized as a market leader by top industry analysts and is ranked by G2 as the #1 sales onboarding and training product.

Our commitment to innovation has also earned us the "AI-based Sales Solution of the Year" award in the 8th annual AI Breakthrough Awards program (PR Newswire), and a Gold Stevie Award for Sales and Customer Service (Mindtickle)- recognition of our dedication to both product excellence and outstanding customer support.

Job Snapshot

Mindtickle is looking for a Senior Product Manager for Seller Mastery - the team that exists to make every sales rep measurably better at their job:

- AI Roleplays - sellers practice real selling situations against an AI buyer, shaped around their skill gaps, their market and their live deals.

- AI Tutor - each seller gets an interactive personalized learning path built just for them.

Both are built on cutting-edge Agentic AI technology: the system decides what a rep needs based on skill gaps and deal context. It runs the interaction and judges the result.

The hard part is creating a feedback loop that helps a learner improve with every attempt. This involves:

- understanding the task they were doing,

- knowing what success actually takes,

- evaluating how well the task was performed, and

- turning that into feedback they will act on.

You own that loop end to end: product direction, roadmap, customer relationships, and business outcomes.

What's in it for you?

Product ownership

- Own product direction and roadmap — what a rep practises, how each attempt is evaluated, and the feedback that follows.

- Define what good looks like for a given selling task, and earn customer agreement on it rather than asserting it.

- Make improvement visible attempt over attempt, and build the manager- and leader-facing analytics that prove it. Completions and usage are not the outcome.

- Say plainly what the platform is missing when it blocks a customer outcome, and get it prioritised.

Customer and market ownership

- Represent the product yourself in pre-sales, escalations and the hard conversations — not behind an account team.

- Run design partnerships with enablement leaders and senior revenue leaders, and come back with decisions rather than notes.

- Build conviction for new bets and go test the assumptions underneath them.

Go-to-market and stakeholder ownership

- Own the launch with product marketing, sales, enablement and customer success — positioning, messaging, and the internal enablement that makes the product sellable and adoptable.

- Keep stakeholders across the company aligned on what you are building and why, and keep leadership current without being asked.

- Contribute to pricing and packaging, and argue business decisions in terms of deal and renewal impact, not feature counts.

AI-native ways of working

- Treat evaluation as the improvement engine — error analysis, quality baselines, and knowing when a change actually made the output better.

- Prototype several paths quickly instead of debating them at length.

- Work with AI agents in your own practice, and read model output with a sceptical eye.

We'd love to hear from you, if you:

- 6+ years of experience, 4+ as a product manager on technology products, ideally B2B SaaS.

- Built something 0→1 - a company, a product line, a first version, a PM function. That instinct matters more to us than the size of your last org.

- Technical depth - an engineering background (Engineering Degree in Computer Science or related field), past experience in a technical role (software developer or equivalent), or past experience in building products yourself.

- Worked on a B2B SaaS product, so admin surfaces and rollout are familiar problems.

- Took a product to market with marketing, sales, enablement and customer success.

- Owned hard customer and exec conversations - design partners, QBRs, pre-sales, escalations.

- Defined metrics that did not exist yet, and been honest about what the data cannot tell you.

- Clear writing. Most of the influence in this role travels as a document.

Preferred Experience

- Built products that judge people — conversation intelligence, assessments, certification, proctoring, performance or competency scoring.

- Data-heavy B2B products where the buyer, the admin and the end user are three different people.

- Shipped GenAI to production, including the unglamorous parts: evaluation, quality regressions, cost and latency.

- Background in sales enablement, revenue intelligence or corporate L&D.

- Familiarity with what makes AI products fast, reliable and affordable at scale.