Director of Product

Role Overview:

As Director of Product, you will own the vision, strategy, and roadmap for Skan's process intelligence platform. This is the platform that helps the world's largest enterprises see how work actually happens inside their organizations, and act on that understanding. It is technically complex, data-intensive, and genuinely impactful at scale.

We are looking for someone who has spent meaningful time in process mining, process intelligence, or intelligent automation. Not just an awareness of the space, but real product experience in it. You know the gap between a compelling demo and something that actually works in a large enterprise environment. You have shipped products in this domain and have the scars to show for it.

With 12 to 15 years of product experience, including time at AI-native startups, you are comfortable making product calls with incomplete information, working without a lot of support structure around you, and keeping a team focused when everything feels urgent. You are also someone who uses AI tools every day in how you work, not just in what you build. That matters to us.

Key Responsibilities:

Product Vision and Strategy:

• Own the product roadmap for the process intelligence platform, from how we capture and model operational data through to the analytics and prescriptive insights we surface to customers.
• Make clear, defensible decisions on what we build next. You will get input from customers, from sales, from data, and from the competitive landscape. Your job is to synthesize all of that and land on a prioritized point of view.
• Keep the company aligned on product direction. That means being a consistent voice in leadership discussions, not just a person who maintains a roadmap document.
• Know the competitive landscape well. Understand what Celonis, SAP Signavio, UiPath, and the broader BPM and automation ecosystem are doing. Use that knowledge to sharpen Skan's positioning and find the white space.

Product Execution and Delivery:

• Work closely with engineering, design, and data science to turn complex customer problems into product requirements teams can actually build from. Good PRDs, clear acceptance criteria, and regular communication matter here.
• Manage delivery across several workstreams at once, covering process discovery, analytics, conformance, and integrations. Help teams make smart trade-off decisions when timelines get tight.
• Stay engaged with architecture and data model decisions that affect the product. You do not need to write the code, but you need to understand what is being built and why certain technical choices matter at enterprise scale.
• Hold a high bar for user experience. Process intelligence data is inherently complex. Making it feel accessible and actionable to both business users and technical users is one of the harder product challenges in this space.

Using AI in How You Work:

We are an AI company. We expect product leaders to work with AI tools every day, not just build products that use them. This is what that looks like in practice.

• Use LLMs and AI research tools to move faster in discovery. Summarize customer interviews, identify patterns across large volumes of feedback, and sharpen your hypotheses without spending days manually reviewing notes.
• Use generative AI to write better first drafts of PRDs and specifications. Spend your energy making judgment calls and refining thinking, not starting from a blank page every single time.
• Set up workflows to track what is happening in the market. Use AI tools to monitor competitor releases, analyst commentary, and community signals across the process mining and automation space so you are never behind.
• Bring your team along. Help your product managers develop real fluency with these tools, including knowing when to trust AI output and when to push back on it.
• Stay grounded in what AI can and cannot do reliably inside enterprise products. That practitioner perspective will directly shape how we build and talk about AI features in the platform.
• Share what you learn. Recommend tools, document what works, and help build an internal culture of AI-augmented work across the product organization.

Team Leadership:

• Build and grow the product management team. That means hiring thoughtfully, giving people real ownership of meaningful problems, and being the kind of manager whose reports get better over time.
• Set up the operating model. Good product teams do not run themselves. Help establish the rituals, frameworks, and ways of working that let people move fast without losing sight of what matters.
• Create an environment where people are honest about trade-offs, comfortable sitting with uncertainty, and focused on outcomes over activity.

Customer and Commercial Engagement:

• Spend real time with customers. Get into the detail of how they use the product, where it falls short, and what they actually need. Use those conversations to challenge your assumptions, not just confirm them.
• Show up in executive-level customer conversations and sales cycles as a credible product voice. You should be able to walk a customer through where the product is heading and why it matters to their specific business.
• Work with Customer Success to track how customers are getting value from the platform and use those signals to sharpen what we build next.

Cross-Functional Alignment:

• Help Sales and Marketing tell a sharper product story. That means going beyond feature lists and helping them articulate what actually makes Skan different in a crowded market.
• Collaborate with Finance and leadership when business cases need product input, whether that involves pricing, packaging, or expansion opportunities.
• Stay close to what Professional Services and Customer Success teams see on the ground. Some of the most useful product insights come from the people who spend the most time with customers post-sale.

Qualifications and Experience:

• 12 to 15 years of professional experience, with at least 8 years in product management in enterprise software or SaaS.
• You have worked at an AI-native startup. You know what it is like to build under pressure, make product calls without full information, and keep moving without a lot of infrastructure around you.
• Background in process mining, process intelligence, BPM, task mining, or RPA is strongly preferred. Candidates with this domain experience will stand out. If you have worked at companies like Celonis, UiPath, SAP Signavio, ABBYY, Minit, or similar, we want to hear from you.
• Real familiarity with process mining concepts: how event logs work, what conformance checking involves, how process discovery surfaces insights, and what makes process KPIs meaningful to an enterprise buyer.
• You understand how AI and ML get applied in operational intelligence products. Not just the theory. You have worked through the practical realities of model development, validation, and how insights actually reach end users.
• You have shipped products used by large enterprises. You understand procurement cycles, compliance requirements, and what it takes to get something adopted at scale inside a Fortune 500 organization.
• You have led product teams before. People grew under your management. You know how to give teams real ownership while keeping everyone pointed in the same direction.
• You are technically credible. You can have a substantive conversation with engineers and data scientists about architecture decisions, API design, and data pipeline trade-offs without needing someone to translate.
• You use AI tools in your day-to-day work and can speak specifically about what you use them for and what impact they have had. This is a real expectation, not a checkbox.
• You communicate clearly across very different audiences, from a technical spec reviewed by engineers to a roadmap presentation in front of a board.
• You can operate in ambiguous situations without becoming paralyzed. Fast-moving, early stage environments energize rather than frustrate you.

Education:

A bachelor's degree in Computer Science, Engineering, Information Systems, or a related technical field is required. An MBA or advanced degree in a quantitative or business discipline is a strong plus.

What Success Looks Like in the First 12 Months:

• You have built a product roadmap that the whole company believes in and that customers are genuinely excited about.
• You have shipped meaningful improvements to the process intelligence platform that customers are using, talking about, and renewing because of.
• The product team is operating well. People have clear ownership, they are growing in their roles, and there is a culture of honest feedback and continuous learning.
• Skan's process intelligence story is sharper and more differentiated in the market. That is visible in customer conversations, analyst coverage, and competitive win rates.
• You have introduced AI-assisted ways of working into how the team runs discovery, writes specifications, and tracks the competitive landscape. It has made a measurable difference.
• People across Sales, Customer Success, Engineering, and leadership come to you when they need the product perspective. You have earned that trust through good judgment and clear communication.

Skan AI is an equal opportunity employer committed to building a diverse, inclusive, and respectful workplace around the world. We do not discriminate based on race, color, religion or belief, sex (including pregnancy, sexual orientation, gender identity, or gender expression), national origin, ancestry, age, disability, medical condition, genetic information, marital or family status, military or veteran status, or any other characteristic protected by applicable laws in the locations where we operate. We welcome people from all backgrounds and provide reasonable accommodations throughout the hiring process.