Staff AI/ML Product Manager

What you'll do

• Product Execution and Roadmap Contribution: Execute Intelligence platform roadmap and contribute meaningfully to 2026 planning based on customer insights and technical learnings. Own requirements gathering with deep problem understanding, uncovering root needs beyond surface-level requests. Design product experiences that build user trust in AI through transparency, explainability, and graceful failure handling.
• Cross-Functional Stakeholder Coordination: Serve as the primary interface between the Intelligence engineering team and Product, Implementation, Sales, Marketing, and Leadership teams. Filter and prioritize incoming requests from 3 product teams to protect engineering focus while addressing critical needs. Facilitate feedback loops to collect ground truth data, stakeholder validation, and user insights.
• Intelligence Product Development: Partner with the Director of Engineering on project planning and delivery tracking across 3-4 parallel initiatives. Drive iterative development cycles with rapid feedback incorporation, shipping incremental value rather than waiting for perfection. Coordinate data labeling and ground truth collection efforts to improve model accuracy and validate product improvements
• Technical Translation and ML Expertise: Engage with engineers on architecture, data pipelines, and model performance without needing to code. Translate model performance metrics (accuracy, precision, recall) into business impact. Understand ML product lifecycle including data requirements, model training and validation, feedback loops, and continuous learning systems
• Continuous Improvement and Learning: Build feedback loops to continuously improve intelligence capabilities based on ground truth data and user insights. Identify opportunities to leverage intelligence across multiple products and create incremental value through shared learning. Support strategic product decisions with technical insights from hands-on execution

What the right person for this role will have

• 5+ years of product management experience with proven track record of shipping products with measurable business impact in fast-paced environments
• 2+ years shipping ML/AI products with demonstrated understanding of the ML product lifecycle from data collection through model deployment and iteration
• Platform product experience with background working on products or features that serve multiple internal or external customers and managing competing stakeholder needs
• Strong technical aptitude with comfort working in SQL, ability to read Python code, and solid understanding of ML fundamentals including model evaluation and data quality requirements.
• Complex stakeholder management with proven ability to navigate conflicting priorities across multiple teams and organizational levels.
• Excellent communication skills with ability to explain technical concepts to business audiences and translate business needs into actionable technical requirements.
• Bias toward action with comfort operating in ambiguous environments and making decisions with imperfect information

Bonus points if you have

• Experience with data labeling, ground truth collection, or model evaluation workflows in production ML systems.
• Previous work at companies with strong AI product culture such as enterprise ML vendors, AI-native SaaS companies, or companies known for ML excellenceFamiliarity with B2B SaaS metrics, enterprise sales cycles, and customer success dynamics in technical products.
• Vancouver-based or willing to relocate with enthusiasm for hybrid work environment and in-person collaboration.
• Experience with LLMs, RAG architectures, or modern ML infrastructure tools such as vector databases or model monitoring platforms.
• Background in insurance technology, regulated industries, or complex B2B workflows