Senior Technical Product Manager, VendorPM

• You'll need genuine curiosity about how AI models/LLMs, data pipelines, and vendor compliance systems actually work—not just what they do
• We also expect you to actively use AI tools in your own workflow. If you're not already experimenting with Cursor, Claude, or similar tools to accelerate your work, this probably isn't the right fit
• Intensity & Rigor: You operate at high energy with meticulous attention to detail. You think through edge cases before they become production issues. Your PRDs are tight, your tickets are unambiguous, and your stakeholder updates are crisp. You hold yourself to a high standard and it shows in the quality of your work
• Default to Curiosity: You're excited by tough problems, not intimidated by them. When you hit a wall, your instinct is "yes, and" rather than "no, because." You ask questions until you understand how systems actually work—not just what they're supposed to do. You're solution-focused and energized by the puzzle of making complex things simple
• Extreme Ownership: Problems are yours to solve, full stop. You don't wait for permission or point fingers when things break. If something is blocking progress, you find a way around it. If a decision needs to be made, you make it and own the outcome. If you learn new information, you course correct quickly
• 5+ years in product management, with at least 2 years in technically complex environments (APIs, data systems, AI/ML features)
• Demonstrated ability to dive into technical details - you've read API docs, written SQL queries, or debugged integration issues alongside engineers
• Track record of shipping AI-powered or data-intensive products, with experience defining success metrics and evaluation approaches
• Deep knowledge of Jira: You've configured workflows, managed complex backlogs, built dashboards, and used advanced features (automation rules, custom fields, JQL) to create visibility and drive execution
• Active experimentation with AI development tools: You use LLMs in your daily workflow and have hands-on experience with tools like Cursor, Claude, ChatGPT, Lovable, or similar - you understand their capabilities and limitations
• Fluency in databases and BI tools: You're comfortable writing queries, building dashboards, and setting up reports in tools like Metabase, Sigma, Heap, Looker, or similar—you don't wait for a data team to answer your questions
• Strong documentation discipline: Experience writing comprehensive PRDs, technical specs, and process documentation in Notion, Confluence, or similar systems—you believe good documentation is a competitive advantage
• Strong systems thinking: you naturally see dependencies, feedback loops, and second-order effects
• Proven ability to collaborate across engineering, design, data, and business stakeholders
• Comfort with ambiguity and rapid iteration—you make decisions with incomplete information and adjust as you learn
• Familiarity with LLM-based products, RAG systems, or context engineering
• Experience with enterprise sales cycles and complex customer environments

Desirable

• The Senior Technical Product Manager will help drive and execute on the technical product strategy for VendorPM's core platform and AI-powered vendor solutions
• You'll own the intersection of complex technical systems and business outcomes, working across engineering, data, and sales teams to ship features that modernize how property managers work with vendors
• This is not a role for someone who wants to write requirements and hand them off
• You'll dig into database schemas, debug API integrations, and partner directly with engineers to solve hard problems
• You'll bring structure to ambiguity, turning strategic priorities into executable plans while maintaining the flexibility to pivot when you learn something new
• We're building technical products in a regulated, relationship-driven industry
• Own product areas spanning vendor data infrastructure, AI-powered pricing/benchmarking, and compliance management systems
• Define technical requirements that account for data dependencies, integration constraints, and architectural trade-offs
• Translate business objectives into technical roadmaps with clear dependencies and milestones
• Drive features from discovery through launch, partnering with engineering to scope work accurately and identify technical risks early
• Build and maintain evaluation frameworks for AI features—you'll define what "good" looks like and how we measure it
• Own cross-functional coordination across engineering, design, data, and GTM for your product areas
• Establish and improve product development processes that enable accountability without bureaucracy
• Create visibility into progress through documentation, roadmap management, and stakeholder communication
• Work directly with external partners and data sources, navigating integration complexity and compliance requirements
• Evolve how we build products using AI tools—from discovery and documentation to prototyping and validation
• Experiment with and operationalize LLM-based workflows, MCP integrations, and AI coding assistants (Cursor, Lovable, etc.) to accelerate the product development lifecycle
• Define when AI-assisted approaches add value versus when they don't, building team intuition through experimentation
• Stay current on emerging AI tooling and bring relevant innovations back to the team
• You'll own product areas that lay the foundation for agentic procurement—a future where AI handles routine vendor management tasks end-to-end while property managers focus on relationships and exceptions
• Near-Term Roadmap: Vendor data infrastructure and schema design, AI-powered pricing and benchmarking, vendor search and matching algorithms, compliance management systems, and role-based access control
• Data & Systems: You'll help establish how data flows into, through, and out of the platform—cleaning up pipelines, building reporting infrastructure, and extending data access to teams that need it. This includes standing up BI dashboards for Sales, enabling self-serve analytics for internal stakeholders, and ensuring data quality supports both product decisions and customer-facing features
• Agentic Procurement: Designing AI systems and agents to alleviate customer pain points, helping drive data architecture that enables reliable AI decision-making, and defining human-in-the-loop patterns that balance automation with appropriate oversight

• We want to be a surprising and exciting place, but we also want you to know what to expect on your journey, starting with the interview process:
• Interview Process Step 1: Google Meets exploratory call with HR
• Interview Process Step 2: Interview with Co-Founder, COO
• Interview Process Step 3: Assignment
• Interview Process Step 4: Presentation to Panel – Co-Founder, COO & other stakeholders