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The Product Manager owns product planning and execution across the full product lifecycle — gathering and prioritizing customer and market requirements, defining the product vision, establishing product strategy, and working closely with Engineering, Design, Sales, Marketing, and other stakeholders to build and launch successful products and capabilities.
Modern product management moves faster than it used to. We expect our PMs to work fluently with AI tools and with our design system, using both to compress the distance between an idea and something a customer can actually react to. In practice that means synthesizing research in hours rather than weeks, producing clickable prototypes instead of static wireframes, and pressure-testing hypotheses with working artifacts before committing engineering capacity. The bar is not “uses AI” — it is judgment about where AI accelerates the work and where human verification is non-negotiable.
The Product Manager brings the team a deep knowledge of users, the market, how existing products are actually used, and which outcomes matter most. The PM establishes and tests product hypotheses and ensures investments support the company’s overall strategy and goals. Together, Product Management, Design, and Engineering discover, plan, and build effective solutions that deliver on the product vision.
The Product Manager is the evangelist for their product area — providing transparency into the product development process, building alignment across company stakeholders, and effectively sharing the product vision and strategy.
RESPONSIBILITIES
Vision, Strategy & Roadmap
Develop, validate, and communicate the product vision and strategy for your assigned areas.
Own and maintain product roadmaps, communicating status, sequencing, and trade-offs to internal stakeholders.
Partner with Product Leadership to prioritize your area within the overall portfolio, and identify and manage cross-team dependencies.
Participate in product pricing and packaging decisions.
Discovery & Research
Conduct user and market research to build a deep understanding of user and buyer personas, critical customer segments, and the competitive landscape.
Use AI-assisted research and synthesis — interview transcription and thematic analysis, support-ticket and usage-data mining, competitive teardowns — to shorten time-to-insight, while validating conclusions with real customers rather than trusting model output.
Frame explicit hypotheses, define what evidence would disprove them, and run lightweight experiments before large investments.
Work directly with product and usage data — query it, chart it, and size opportunities without waiting on an analyst.
Design, Prototyping & Definition
Partner with Design on exploratory, interaction, and fit-and-finish work.
Build your own low- and mid-fidelity mockups and clickable prototypes using our design system and AI-assisted prototyping tools — enough fidelity to test a concept with customers and align stakeholders, with craft-level design owned by Design.
Treat the design system as a shared language: compose from documented components and tokens, reuse established patterns, and surface gaps rather than inventing one-off solutions.
Translate user needs into crisp problem statements, user stories, and acceptance criteria. Use AI to draft and stress-test these artifacts — and own their final quality and accuracy.
Delivery
Participate with Engineering in the agile sprint process, including sprint planning, backlog refinement, and retrospectives.
Lead prioritization and backlog management for your area, serving as the primary point of contact for technical teams.
Favor small, frequent releases over big-bang launches — use feature flags, staged rollouts, and internal dogfooding to learn quickly and de-risk delivery.
Establish product goals, and set and track the metrics that show whether they were met.
Launch & Adoption
Lead the product launch process for new products and capabilities in collaboration with Marketing, Sales, Support, and Customer Success.
Equip product launch teams with the positioning, demos, and enablement material they need — and stay accountable for adoption after launch, not just the ship date.
Close the loop: monitor post-launch metrics and customer feedback, and feed what you learn back into the roadmap.
SKILLS AND EXPERIENCE 3+ years of experience in agile product management.
Deep understanding of product management methodologies across discovery, prioritization, and delivery.
Demonstrated fluency using AI tools in day-to-day product work — research synthesis, drafting and stress-testing specs, prototyping, data analysis — with sound judgment about where AI output requires human verification.
Hands-on ability to produce mockups and interactive prototypes using a design system and modern prototyping tools (e.g., Figma, component libraries, AI prototyping tools). You do not need to be a designer; you do need to be able to show, not just tell.
Comfort working with data — able to write or generate queries, read dashboards, and quantify an opportunity independently.
Experience conducting user and market research and synthesizing needs and opportunities.
Superior communication skills to evangelize your product area and articulate user and business needs.
Ability to identify and work with Design and Engineering to solve ambiguous problems.
Self-motivated, with strong task and time management skills.
NICE TO HAVE Experience shipping AI- or ML-powered product capabilities, including the harder parts: evaluation, accuracy thresholds, human-in-the-loop design, and earning user trust.
Background in B2B or enterprise SaaS, particularly in logistics, supply chain, or financial operations.
Familiarity with feature flagging, A/B testing, and continuous delivery practices.
Experience partnering with data or platform teams on API- and integration-heavy products.