Job Title

The Vice President of Engineering will partner with the founders and product leadership to build the engineering organization that takes VendorPM to its next stage of growth. You''''ll report directly to the COO and own technical architecture, engineering culture, and delivery execution. We''''ve moved fast and hit our growth stride with signed enterprise customers, and built a platform that 10,000+ buildings and 70,000 vendors depend on daily. That speed created a strong foundationand also the kind of technical and process debt you''''d expect from a company that prioritized shipping over polish. Now we need a leader who can build the engineering maturity and discipline to support the next phase: larger customers, more complex requirements, and a product vision centered on agentic procurement. This is a hands-on leadership role. You''''ll update code standards, make architectural decisions you can defend technically, and work directly with engineers to solve hard problems. But you''''ll also shape the longer-term visionbuilding toward AI systems that handle routine vendor management tasks end-to-end while making nuanced judgment calls about when to pay down debt, when to refactor, and when to ship. You''''ll join a company with strong product leadership, a clear strategic direction, and founders who are deeply involved in the business. What we need is an engineering leader who can match that clarity on the technical sidesomeone who can build a culture of ownership, quality, and velocity that scales with us. We expect you to be hands-on with AI tooling. If you''''re not already using Cursor, Claude, or similar tools to accelerate your own work and thinking about how AI changes engineering team productivity, this isn''''t the right fit. What we are looking for Deep experience (10-15 years) building or significantly improving an engineering organizationyou''''ve shaped culture and process, not just inherited a working machine Deep technical fluency with modern web architecturesyou''''ve built and scaled systems on AWS/GCP with Node.js/TypeScript, GraphQL, React, and PostgreSQL Track record of improving engineering delivery predictability and quality while maintaining team morale and velocity Handson leadership styleyou stay close to the code and can contribute technically when needed Experience integrating AI/ML capabilities into production systems Comfort with ambiguity and competing priorities: you''''ve worked in startups or growthstage companies where judgment matters more than playbooks Strong opinions on engineering culture and process, informed by experience with what actually works What youll be doing Technical Leadership Own architectural decisions across our platformyou''''ll need to understand our NestJS/PostgreSQL/Apollo GraphQL/React stack deeply enough to guide its evolution and make buildvsbuy decisions Drive the technical strategy for AI integration, including evaluating when to extend our TypeScript stack versus introducing Python or other languages better suited for AI/ML and dataintensive workloads Make nuanced tradeoffs between paying down technical debt and shipping featuresand build team judgment for making these calls well Lead a team of ~10 engineers and set the bar for what great engineering looks like at VendorPMwe believe strong engineering culture is built through inperson collaboration, whiteboarding sessions, and solving hard problems together Shift team structure and processes toward true fullstack ownership, moving away from rigid frontend/backend distinctions that create handoff friction and limit engineer growth Build processes that create accountability and visibility without bureaucracysprint planning, estimation, and delivery tracking that enable engineers to own outcomes, not just tasks AI-Forward Development & QA Practice Establish practices for AIassisted development across the engineering teamwe expect engineers to leverage tools like Cursor, Claude, and Copilot to accelerate their work Build QA and testing approaches that account for AIgenerated code: review practices, test coverage expectations, and quality gates that maintain standards while capturing productivity gains Evaluate and integrate AI tooling into CI/CD, code review, and documentation workflows where it adds genuine value Delivery & Execution Own engineering delivery against product roadmap commitments with realistic estimation and clear communication when plans change Partner with Product on technical discovery to identify architectural prerequisites and risks before work enters sprints Build the muscle for shipping reliablywe want a team that hits its commitments and knows how to scope appropriately What Youll Work On NearTerm (Q1Q2 2026): Compliance system evolution: Our compliance domain is central to the product and needs architectural improvement to support buildingspecific requirements and clearer data models Rolebased access control (RBAC): Solution is designed and ready for executionneeds engineering leadership to ship well Vendor data model improvements: Evolve our vendor data model to support the complexity of how enterprise PMCs categorize and manage vendors Engineering process foundations: Implement sprint planning, backlog management, and delivery practices that create predictable output MediumTerm: AI infrastructure: Extend our AI assistant capabilities, improve document parsing accuracy, and build the foundation for agentic procurement features Integration platform: Build robust patterns for ERP integrations (Yardi, MRI) that scale across customers Platform scalability: Address performance and architecture needs as we grow into larger enterprise deployments The Bigger Picture: You''''ll help build toward agentic procurementa future where AI handles routine vendor management tasks endtoend while property managers focus on relationships and exceptions. That vision requires thoughtful architectural decisions today, and an engineering organization capable of building sophisticated AIpowered features reliably. What We Value Intensity & Rigor: You operate at high energy with meticulous attention to detail. You think through edge cases before they become production issues. Your architectural decisions are defensible, your code reviews are thorough, and your team communications are crisp. You hold yourself to a high standard and it shows in the quality of what your team ships. 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 dig into systems until you understand how they actually worknot just what they''''re supposed to do. You''''re energized by the puzzle of making complex things simple and you build teams that think the same way. 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 quicklyand you build a team culture where everyone operates the same way. Bonus If You Have Experience in PropTech, real estate, or B2B marketplaces Background with compliance systems, credentialing, or multisided platforms Handson experience with LLMbased features, RAG systems, or AI agents in production Experience building hybrid TypeScript/Python architectures for AIintensive applications Experience preparing engineering organizations for significant scale or exit Whats In It For You Equity Meaningful ownership in what you help build InPerson, HighEnergy Environment: Our downtown Toronto office is where the work happens. We''''re an inperson company because we believe the best engineering culture is built through realtime collaborationwhiteboarding, pair programming, and solving hard problems together. 4 weeks vacation + wellness days Employer topup for maternity and parental leave Regular team events and a closeknit culture Interview Process Interview process step 1: Google Meets call with Recruiter Interview process step 2: Interview with the Hiring Manager Interview process step 3: Technical Interview with Product Consultant Interview process step 4: Take home assignment Interview process step 5: In office meet the team Notes: This posting is for a current opening Artificial intelligence (AI) is not used at any stage of the hiring process for this role. All applications are reviewed, assessed, and selected by real people. We are committed to a fair and transparent hiring process. We are committed to providing an inclusive, accessible environment where all employees and clients feel valued, respected and supported. We aim to build a workforce that reflects the diversity of our communities, and to create an environment where every employee has the opportunity to reach their potential. #J-18808-Ljbffr