DataStealth Principal Technical Product Manager — AI, DSP & DSPM Mississauga, ON · Hybrid or Remote Across CAN/US/EU· Full-time · Product · Reports to the Director of Product Management ABOUT DATASTEALTH DataStealth is a single, unified AI data security platform (DSP) that discovers, classifies, and protects sensitive data across your entire environment — from on-premise to legacy systems to cloud. Wherever your data lives or flows, we protect it using the latest technologies and AI. We do this without requiring complex integrations or changes to your existing applications, ensuring security that enables, rather than hinders, your business. By seamlessly applying data protection strategies such as tokenization, we ensure that even if your perimeter is breached, your data remains unusable if it falls into the wrong hands. Recognized for the fifth consecutive year as a Great Place to Work, we are one of the world's leading and fastest growing cybersecurity software companies. Our patented technology gives our large enterprise customers a paradigm-shifting way to solve the data security problems that legacy approaches cannot. ABOUT YOU You are a rare superset: a product leader who is as comfortable in the architecture review as in the customer's boardroom. You read the architecture diagram, follow the data flow, and reason about how sensitive data is discovered, classified, and protected across a sprawling enterprise estate — and you also own the business: the market, the buyer, pricing and packaging, and the commercial outcomes your product drives. You earn your seat with engineering through technical credibility, and your seat with the executive team through commercial judgment. You have built security or data products, and you have shipped AI/ML into something real — ideally agentic systems that take action, not just dashboards. You can tell the difference between AI that creates customer value and AI that creates risk, and you have clear opinions on where AI in security is genuinely heading. In the same week you might defend a multi-quarter roadmap to leadership, whiteboard an agent workflow with engineers, run a discovery call with a CISO, and sit with a design partner's security team to understand why the deal hinges on one capability. You do not see business and technical depth as a trade-off — you carry both. ROLE OVERVIEW The Principal Technical Product Manager is the most senior individual-contributor product role on the DataStealth Data Security Platform (DSP) and our Data Security Posture Management (DSPM) capabilities — how we discover, classify, prioritize, and protect sensitive data across cloud, hybrid, and on-premises estates, and how AI agents do that work autonomously and safely. This is a superset role: you own the full product, end to end, from market and customer strategy through technical architecture and delivery. Reporting to the Director of Product Management, you own strategy, roadmap, and execution for your domain. You own the business and customer side — the market, the buyer, positioning, pricing and packaging, and the commercial outcomes — and you own the technical side at the depth this platform demands: operating at the architecture level with engineering, writing specs precise enough to build from, and prototyping or pressure-testing the riskiest ideas before the team commits. Most product roles do one of these well; this role requires both. You partner with the Director of Product Management and the broader product team on strategy, with the CTO and engineering leadership on platform direction, and day-to-day with Engineering, Design, Sales, and Customer Success. As the principal product voice in your domain, you also raise the bar for the craft of other PMs through exemplar specs, discovery practice, and mentorship. WHAT YOU WILL DO PRODUCT STRATEGY FOR AI-BASED DSP & DSPM - Own the strategy, roadmap, and execution for the AI-First Data Security Platform and our Data Security Posture Management capabilities — data discovery, classification, sensitivity and risk scoring, posture visibility, and automated remediation across AI, cloud, hybrid, and on-premises estates. - Make AI-driven discovery and classification the core of the product: ML- and LLM-based classifiers, embedding similarity, and context-aware sensitivity detection that find sensitive data wherever it lives — going well beyond regex and pattern matching in accuracy and coverage. - Drive autonomous and bot-driven capabilities in the solution — continuous scanning bots, auto-tagging and auto-classification, and policy-driven remediation that acts on findings with the right guardrails and human oversight. - Champion an API-native, headless platform — every capability exposed through clean, well-documented APIs so the product integrates into customers' existing applications and pipelines, and so AI agents can consume and operate it natively as first-class users. - Turn the hardest customer data-security problems into a clear, sequenced roadmap, balancing differentiation, parity, and platform health with defensible trade-offs. - Run discovery end to end: customer and design-partner interviews, win/loss and support signals, competitive teardowns, and usage data — and convert them into prioritized, well-scoped bets. - Define what success looks like for AI features: classification accuracy and coverage, false-positive cost, adoption and activation targets, and the leading indicators that show a capability is landing before revenue confirms it. BUSINESS, MARKET & CUSTOMER OWNERSHIP - Own the commercial outcomes of your domain — understand the market, the buyer (CISO, security and data-governance leaders), and the competitive landscape well enough to make sharp positioning and investment calls. - Drive pricing and packaging in partnership with leadership, and tie roadmap decisions to revenue, retention, and expansion — not just