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Product Manager - AI Observability​/Evaluation Platform

Job in Toronto, Ontario, C6A, Canada
Listing for: Spotify
Full Time position
Listed on 2026-02-27
Job specializations:
  • IT/Tech
    AI Engineer, Machine Learning/ ML Engineer, Data Science Manager, Product Engineer
Salary/Wage Range or Industry Benchmark: 140222 CAD Yearly CAD 140222.00 YEAR
Job Description & How to Apply Below

Why consider this job opportunity

  • Salary up to 140,222 CAD plus equity
  • Opportunity for career advancement within a leading technology company
  • Flexible work environment allowing for a mix of in-office and remote work
  • Supportive culture promoting inclusivity and diverse perspectives
  • Chance to work with cutting‑edge ML and AI technologies
  • Access to reasonable accommodations during the recruitment process
What to Expect (Job Responsibilities)
  • Own the product roadmap for AI observability capabilities, including instrumentation and debugging workflows
  • Collaborate with stakeholders to develop AI/Agentic evaluation capabilities
  • Build instrumentation defaults that enhance observability of LLM workloads
  • Partner with engineering to establish root‑cause workflows across LLM chains
  • Define and track success metrics related to product performance and compliance
What is Required (Qualifications)
  • 2+ years of experience as a Product Manager, Technical Product Manager, or in a similar product ownership role
  • Familiarity with ML and AI development processes and LLM application patterns
  • Understanding of LLM evaluation approaches and methodologies
  • Comfortable collaborating with engineers on technical tradeoffs and system design
  • Strong skills in product discovery, prioritization, and stakeholder alignment
How to Stand Out (Preferred Qualifications)
  • Experience working with ML/AI technologies in a product management capacity
  • Knowledge of metrics‑oriented approaches to product development and iteration
  • Proven ability to communicate effectively with technical and non‑technical stakeholders
  • Background in data science or related fields

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