Top Entry Level Product Manager Jobs in Seattle, WA

Own Flodesk’s AI product behavior and quality systems across prompt creation, agentic editing, and future marketing workflows. Develop and version prompts, define context and acceptance criteria, build evaluation datasets and rubrics, monitor quality, review traces, diagnose failures, and establish release gates. Translate research, analytics, support feedback, and production issues into priorities and experiments while partnering with engineering, design, marketing, copy, and product teams.

Own product areas for KIRA’s AI stockbroking and financial services applications. Define user problems, product scope, success metrics, roadmaps, and launch plans. Collaborate with engineering, design, data, operations, compliance, and business teams to simplify complex financial products. Launch features, monitor performance, use research and feedback to guide iterations, and balance speed, user experience, business impact, compliance, and operational complexity.

Own Prendio’s data product strategy from discovery through commercialization. Define valuable data assets, build the roadmap, validate customer needs, develop packaging and pricing, and launch revenue-generating products. Partner closely with engineering, analysts, data teams, sales, and marketing; prototype concepts independently; manage delivery; and address privacy, contractual, regulatory, and data-rights constraints. The role initially focuses on biotech customers and may expand to supplier-side products.

Own the strategy, roadmap, business performance, and value delivery for WebCenter PLMS, an enterprise SaaS product serving regulated Life Sciences customers. Translate customer and regulatory needs into prioritized requirements, initiatives, and product investments. Lead discovery, business cases, launches, adoption, pricing, positioning, partnerships, and cross-functional alignment with Product, R&D, Sales, Marketing, and regional teams. The role is remote within the US Eastern time zone, with approximately 10% travel and an onsite immersion program.

Own product areas for an AI-powered neobank across insurance, payments, savings, investing, travel, and other financial services. Define user problems, product scope, metrics, roadmaps, and launch plans; collaborate with engineering, design, data, operations, compliance, and business teams; simplify complex financial workflows; and use research, feedback, experiments, and performance data to drive continuous product improvements.

Own AI Investing product areas across financial services, defining user problems, product scope, metrics, roadmaps, and launch plans. Collaborate with engineering, design, data, operations, compliance, and business teams to simplify complex financial journeys. Use data, research, feedback, experiments, and production issues to guide decisions, launch features, monitor performance, and drive continuous iteration while balancing speed, user experience, business impact, compliance, and operational complexity.

Own AI Finance product areas across insurance, payments, savings, investing, travel, and related services. Define user problems, product scope, metrics, roadmaps, and launch plans; collaborate with engineering, design, data, operations, compliance, and business teams; simplify financial workflows; analyze feedback and performance; and continuously iterate while balancing speed, user experience, business impact, compliance, and operational complexity.

Own product areas within BJAK’s AI Stockbroking and broader financial services portfolio. Define user problems, product direction, scope, metrics, roadmaps, and launch plans. Collaborate with engineering, design, data, operations, compliance, and business teams to simplify complex financial products, launch features, monitor performance, and iterate based on data, research, feedback, and production issues. Balance speed, user experience, business impact, compliance, and operational complexity.

Own product areas within AI Investing and related financial services, defining user problems, product direction, roadmaps, metrics, and launch plans. Collaborate with engineering, design, data, operations, compliance, and business teams to simplify complex financial products. Launch features, monitor performance, use data and feedback to drive iterations, and balance speed, user experience, business impact, compliance, and operational complexity.

Own AI Finance product areas across insurance, payments, savings, investing, travel, and other financial services. Define user problems, scope, metrics, roadmaps, and launch plans; collaborate with engineering, design, data, operations, compliance, and business teams; simplify complex financial journeys; and use research, feedback, experiments, and performance data to iterate rapidly after launch.

Own and manage a digital commerce product area end to end, focusing on top-of-funnel experiences such as browsing, search, and product pages. Analyze APIs, microservice contracts, data flows, backend batch jobs, page data, and analytics tags. Apply agile digital operations using Azure DevOps, perform basic financial analysis, and work with digital retail technologies including search platforms, CMS, APIs, and service layers.

Own the end-to-end Service Experience product strategy and roadmap for a two-sided home-services marketplace. Lead AI-powered customer and Pro support, evaluation systems, trust and conflict-resolution policies, and AI-driven experience innovation. Own Contribution LTV and brand-promise metrics, prototype with LLMs, analyze transcripts and data, and influence senior leaders and cross-functional peers without direct reports. Success includes scaling high-quality AI resolution, improving profitability and service outcomes, and delivering an AI experience proof of concept.

As the Founding Product Manager at Freeflow, you will define AI-driven products for the insurance industry, focusing on claims auditing solutions, enhance efficiency and collaborate closely with teams and users to translate pain points into deliverables.

Owns the end-to-end product strategy and execution for AI-powered systems. Defines requirements, evaluation frameworks, quality standards, and system behavior while balancing quality, latency, cost, reliability, safety, and user experience. Partners closely with ML, backend, and client engineering teams to identify failure modes, improve model performance, prioritize roadmaps, and deliver predictable, useful, trusted AI experiences.

Join Databricks' 2027 APM cohort to own end-to-end product projects: understand customer problems, prototype and validate ideas, work with engineers and designers to build and launch features on the Databricks platform, and iterate using data-driven feedback.