Coding agents are only as good as the context they're given. Most explore a repository like a new hire on day one—grepping, opening files and guessing. JetBrains Context replaces that with actual knowledge of the whole codebase and its resources, served to any agent that asks. This role owns the layer that decides what an agent knows before it writes a single line.
JetBrains creates intelligent software development tools for developers and teams. More than 15 million users, over 300,000 companies and 88 of the Fortune Global Top 100 rely on its products to solve complex problems. Its mission is to make development teams more productive and AI adoptable at scale.
As agents improve at searching for themselves, the role will define the durable value of a managed retrieval layer and own JetBrains Context as a product—defining what it is for, who it is for, how success is measured and where it goes next. This is a hands-on role managing the product from a terminal and agent session rather than slides. It bridges the technical core and cross-functional teams, collaborating with engineering and ML teams on indexing pipelines and retrieval quality; working with Air, IDE and Junie teams on integrations; and partnering with marketing, developer advocacy, sales and customer success on positioning and adoption. The role has full ownership of defining problem statements, setting explicit trade-offs and balancing cost, latency and freshness across the platform.
Responsibilities include building and maintaining a deep working understanding of chunking, embeddings, index freshness, retrieval, reranking and agent-facing surfaces; defining and defending an opinionated product vision with clear target audiences, use cases and success metrics; and translating product strategy into actionable problem statements, priorities, plans and milestones with an explicit definition of done. The role will communicate product direction to engineering, leadership, cross-functional stakeholders, customers and prospects; analyse competing context and code-search products through direct use; define operational and product metrics covering index freshness, retrieval quality, agent task outcomes, adoption, retention and unit economics; represent the product externally through roadmaps, published updates, talks and community feedback; and partner with ML teams on model evaluation and platform teams on service scale, reliability and cost.
The successful candidate will have a well-argued point of view on AI-first development and what agents need from a context layer; technical depth across embeddings, retrieval quality, sub-agents, tool-calling, indexing costs and API design; and the habit of using the product they build alongside competitors' tools. They will communicate effectively with audiences ranging from staff engineers and enterprise architects to conference attendees, take a data-informed approach combining telemetry, evaluation results, customer conversations and market signals, and be comfortable defining a new category amid ambiguity.
Applicants need proven experience owning a complex developer, platform or infrastructure product end to end, including strategy and roadmap; hands-on familiarity with modern AI coding tools and agent workflows; the technical capability to work directly with engineering on retrieval behaviour, APIs, data models and integration surfaces; the ability to define metrics for quality-sensitive products and build evaluation habits that maintain product standards; and experience communicating a product externally through written content, talks or community engagement. Practical experience with search, retrieval, RAG, developer search or static analysis at scale is a plus.
In the first months, the successful candidate will form and share a clear thesis for what JetBrains Context is and is not, establish metrics that distinguish real retrieval quality from vanity usage, create a roadmap with clear trade-offs and document an evaluation of serious competitors. Longer-term success means JetBrains Context becomes a deliberate choice for developers and organisations, agents get measurably better answers, enterprises adopt it for its governance and scale, and the market understands its unique value.
JetBrains offers a strong base salary and competitive pay reflecting skills and experience; flexible work from home or from the office; the option to work remotely from abroad for up to 30 days per year; extra time off; a medical insurance allowance; learning and development opportunities including conferences, courses and language classes; language classes; a hot meal or lunch allowance on workdays; mental health support; a sports benefit; and internal events. Some benefits may vary by location.