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GitKraken is a developer experience platform used by over 40 million developers and 100,000 organizations, offering built-in AI and workflow orchestration across desktop, CLI, IDE, web, and mobile with various integrations. They’re hiring Full Stack Product Engineers for GitKraken Insights, a new engineering intelligence product that helps leaders understand how work moves through teams—covering PR flow, DORA metrics, code quality, developer sentiment, AI tool adoption, and bottlenecks—built with React, Go, PostgreSQL, AWS, and GitHub workflows. You’ll turn ambiguous product ideas into technical plans and end-to-end features, build interfaces for complex engineering data, shape the product area with customer demand, and design APIs, data models, and experiences for engineering intelligence workflows. Required qualifications include product judgment, full-stack production software experience, Go or the ability to ramp quickly, API design with contracts and error handling, experience with AI coding agents, Git/GitHub/CI/CD, PostgreSQL fundamentals, React and TypeScript, and clear written communication; bonus points for broader full-stack data experience and additional AI tool usage. Benefits include competitive compensation, flexible PTO, parental leave, health/dental/vision insurance, 401(k) with company match, travel benefits after 1 year and every 5 years, and a remote or hybrid work option in Scottsdale, AZ (Phoenix area), with equal opportunity and a focus on diversity.

GitKraken is a developer experience platform used by over 40 million developers and 100,000 organizations, combining built-in AI and workflow orchestration to streamline collaboration and boost productivity across desktop, CLI, IDE, web, and mobile. The company is seeking a pragmatic Senior Machine Learning Engineer or Applied Data Scientist to take ideas from concept to production, owning end-to-end data work and delivering measurable impact without waiting for perfect specs. Responsibilities include identifying high-value opportunities from product, customer, and operational data, building practical 80/20 solutions, integrating models with production systems, and defining success metrics to drive real-world outcomes. The role emphasizes cross-stack work with a tech lens that includes Python for data/ML, Go and TypeScript for core product, Snowflake, AWS, and Datadog, and AI tools like Cursor, Claude Code, and Codex. Qualifications include deep ML/AI experience, a track record of shipping data-driven features, comfort with ambiguity, strong communication, and ownership, with generous compensation, benefits, and growth opportunities.