Senior Product Manager, AI and Analytics

Intelex Technologies is a global leader in software solutions for Environment, Health, Safety and Quality (EHSQ) programs. They are seeking a Senior Product Manager, AI and Analytics to lead the product vision and roadmap for AI capabilities across their platform, working closely with engineering and design teams to deliver impactful analytics features.

Responsibilities:

• Define and maintain the product roadmap for AI and analytics capabilities, balancing near-term customer value with long-term platform differentiation
• Translate business objectives, market signals, and customer research into a prioritized backlog with clear goals, success metrics, and release milestones
• Develop and communicate a compelling product vision for how AI—including LLMs, Auto-Structure, AI Lens, and agentic workflows—will transform how EHSQ professionals work
• Partner with the VP of Data Analytics, Architecture & AI to align AI product investments with company strategy and Fortive Business System priorities
• Identify opportunities to leverage Intelex’s unique cross-industry EHSQ data as a strategic moat, and build products that capitalize on it
• Conduct ongoing customer discovery—through interviews, advisory councils, and collaboration with sales and customer success—to deeply understand EHSQ workflows and unmet needs
• Analyze usage data, NPS feedback, and support signals to identify friction points and validate hypotheses before committing to development
• Track the competitive landscape across EHSQ software, EHS AI point solutions, and horizontal AI platforms to surface gaps and positioning opportunities
• Partner with marketing on positioning, messaging, and analyst relations (e.g., Verdantix, Gartner) for AI and analytics features
• Own the end-to-end delivery of AI and analytics features—from writing clear PRDs and acceptance criteria through sprint planning, launch, and post-release iteration
• Collaborate closely with engineering leads, AI Solution Architects, and UX designers to make sound build-vs-buy-vs-partner decisions and ensure technical feasibility
• Define instrumentation and analytics strategies so new AI features are measurable from day one; monitor adoption, quality, and outcome metrics post-launch
• Manage dependencies across squads and proactively surface risks to delivery timelines
• Support customer onboarding and enablement by working with the services team to define configuration guides, training materials, and rollout playbooks for AI capabilities
• Serve as the internal product authority on AI and analytics—enabling sales, presales, and customer success teams with competitive positioning, demo narratives, and feature deep-dives
• Present roadmap updates, business cases, and launch readiness reviews to senior leadership, including the CPTO and executive team
• Represent the voice of the customer in architecture and governance reviews, ensuring AI design decisions preserve trust, explainability, and regulatory compliance
• Contribute to Intelex’s external AI narrative—including customer-facing trust and governance documentation, AI pricing strategy, and partner/ecosystem communications

Requirements:

• 5+ years of product management experience, with at least 2 years focused on AI, data, or analytics products in a B2B SaaS environment
• Demonstrated track record of taking AI or data-driven features from discovery through launch and measuring their business impact
• Experience working directly with data science, ML engineering, or AI architecture teams and translating technical constraints into clear product decisions
• Strong command of agile methodologies and experience managing a backlog across multiple concurrent workstreams
• Bachelor's degree in Business, Computer Science, Information Systems, Engineering, Data Science, or a related field
• 7+ years of product management experience, including at least one senior or lead PM role
• Experience in enterprise EHSQ, ERP, compliance, or related regulated-industry software
• Background in or exposure to data product management, including working with structured and unstructured data transformation pipelines
• Familiarity with AI platform economics, usage-based pricing models, or AI add-on packaging in enterprise SaaS