Senior Product Manager

Terzo is an enterprise company that transforms unstructured commercial data into a structured Financial Intelligence Graph, helping organizations manage contracts and vendor relationships. As a Senior Product Manager, you will own product strategy and execution, working closely with enterprise buyers to solve complex problems and improve financial outcomes.

Responsibilities:

• Own product strategy and roadmap across key areas of the Terzo platform, from AI-powered workflows and analytics to the Financial Intelligence Graph and NirvanAI experiences
• Translate ambiguous enterprise problems into clear, well-scoped requirements and make hard prioritization calls without waiting to be told what matters
• Define how AI capabilities, structured graph data, and agentic workflows surface as experiences that feel simple and trustworthy to enterprise users
• Partner closely with engineering to shape platform and experience-level tradeoffs
• Partner with design to define end-to-end user flows, interaction models, and AI-native UX patterns where clarity and trust are non-negotiable
• Work directly with customers to validate problems, test solutions, and measure impact
• Serve as the product voice in sales and pre-sales conversations, building credibility with CFOs, CPOs, and General Counsels
• Define success metrics tied to customer outcomes, adoption, and financial value
• Drive execution end-to-end from discovery through launch and iteration, with clear accountability and no hand-holding required
• Align stakeholders across engineering, sales, customer success, and leadership
• Use usage data, customer feedback, and market signals to continuously sharpen product direction, not just confirm it

Requirements:

• 5 to 8 years of product management experience in B2B or enterprise SaaS
• Experience owning complex enterprise software products end to end, with meaningful UX complexity
• Proven ability to lead products from concept through scaled adoption
• Deep enough technical fluency to co-design system approaches with engineering, understand AI product tradeoffs (RAG, agentic architectures, evals), and influence platform direction without waiting for engineering to prescribe it
• Experience defining AI product requirements including evaluation criteria, fallback behaviors, and human-in-the-loop design. You understand the difference between deterministic software and probabilistic AI outputs, and you hold AI features to a standard accordingly
• Strong UX sensibility: you can write product specs that feel designed, push back on interfaces that create confusion, and hold a high bar for how information and AI outputs are presented to users
• Experience defining end-to-end user flows across data-heavy, workflow-driven products where clarity and trust are non-negotiable
• Proven ability to translate complex data and AI outputs into experiences that feel simple and actionable to enterprise users
• Skilled at running structured customer discovery: interviews, usability walkthroughs, and feedback loops that directly shape what gets built
• Comfortable serving as the product voice in customer and prospect conversations, building credibility with CFOs, CPOs, and General Counsels through domain fluency and product conviction, not just product demos
• Uses prototypes and working concepts in customer conversations to test hypotheses before engineering starts
• Strong ownership mentality with accountability for outcomes
• Clear, structured thinking and written communication
• Comfort operating in ambiguous environments with evolving inputs
• Ability to influence without authority across engineering, design, and customer teams
• Writes PRDs, strategy memos, and specs that are precise enough for engineering to start without a meeting to explain them
• Treats post-launch measurement as a discipline, not an afterthought. Defines success metrics before shipping, tracks them after
• Experience in CLM, procurement, spend management, or financial operations
• Prior work on analytics platforms, financial systems, or commercial operations tools
• Hands-on experience with AI and ML teams shipping applied intelligence products in production, including defining evals, working with model outputs, and iterating on AI feature quality
• Familiarity with platform ecosystems, integrations, or marketplace models
• Prior work at a high-growth startup (Series A to C) where you helped build product function from the ground up, not just inherited a mature process
• Experience with graph data models, knowledge graph systems, or structured commercial data