product manager in AI coding agents

JetBrains creates intelligent software development tools for developers and teams. Its products help more than 15 million users and over 300,000 companies solve complex problems, with the mission of making development teams more productive and AI-adoptable at scale. JetBrains Context provides coding agents with knowledge of an entire codebase and its resources.

• Build and maintain a deep working understanding of chunking, embeddings, index freshness, retrieval, reranking, and agent-facing surfaces;
• Define and defend a vision for the product’s evolution, including target audiences, use cases, and success metrics;
• Translate product strategy into actionable problem statements, priorities, plans, and milestones with a clear definition of done;
• Communicate product direction to engineering, leadership, cross-functional stakeholders, customers, and prospects;
• Analyze competing context and code-search products through direct use to establish differentiators and identify gaps;
• Define operational and product metrics, including index freshness, retrieval quality, agent task outcomes, adoption, retention, and unit economics;
• Represent the product externally by sharing roadmaps, publishing updates, speaking to developer audiences, and gathering community feedback;
• Partner with ML teams on model evaluation and platform teams on service scale, reliability, and cost;
• Own JetBrains Context as a product by defining its purpose, audience, success measures, and future direction;
• Collaborate with engineering and ML teams on indexing pipelines and retrieval quality;
• Work with Air, IDE, and Junie teams on integrations;
• Partner with marketing, developer advocacy, sales, and customer success on positioning and adoption;
• Define problem statements, set explicit trade-offs, and balance cost, latency, and freshness across the platform;
• Develop and share a clear product thesis, establish metrics that distinguish retrieval quality from vanity usage, create a roadmap with clear trade-offs, and document competitor evaluations;
• Drive product adoption by helping agents provide better answers, supporting enterprise governance and scale, and communicating the product’s value to the market.

• Bring a well-argued point of view on the future of AI-first development and what agents need from a context layer;
• Have technical depth across embeddings, retrieval quality, sub-agents, tool-calling, indexing costs, and API design;
• Use the product being built daily alongside competitors’ tools;
• Communicate effectively with audiences ranging from staff engineers and enterprise architects to conference attendees;
• Use telemetry, evaluation results, customer conversations, and market signals to inform decisions;
• Be comfortable with ambiguity and prefer defining a new category over copying an existing one;
• Have proven experience owning a complex developer, platform, or infrastructure product end to end, including strategy and roadmap;
• Have hands-on familiarity with modern AI coding tools and agent workflows;
• Be able to work directly with engineering on retrieval behavior, APIs, data models, and integration surfaces;
• Be able to define metrics for quality-sensitive products and establish evaluation practices that maintain product standards;
• Have experience communicating a product externally through written content, talks, or community engagement;
• Nice to have: practical experience with search, retrieval, RAG, developer search, or static analysis at scale.

• Strong base salary; competitive pay reflecting skills and experience;
• Work from home or from the office;
• Remote work from abroad for up to 30 days per year;
• Extra time off;
• Medical insurance allowance for the employee and family;
• Access to conferences, courses, and language classes;
• Hot meals or a lunch allowance on workdays;
• Access to professional mental health services;
• On-site gym or sports club stipend;
• Company-wide celebrations and team gatherings;
• Some benefits may vary depending on location.