Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic's complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI.

The Context

Engine team builds the knowledge layer that AI agents use to work with enterprise data in Elasticsearch. We extract knowledge from any data sources into a structured AI Index, serve it to agents through public APIs, MCP tools and framework integrations, and close the loop with agent traces so that what the engine knows improves from real usage. This is a hybrid role at the intersection of engineering, data science, and product.

You will work alongside data scientists, backend engineers, product, and UX, and your work will show up directly in what customers build on top of Elastic. The codebase is TypeScript and we build it in the open, so you'll be shipping code, designs and discussions in public alongside the rest of the Elastic Stack.

Define how we iterate on agents and skills safely: versioning and rollout of prompts, skills and automations, regression coverage, staged and shadow evaluation, and the guardrails that let us change behaviour without breaking customers. Design the telemetry we need to make data-informed engineering decisions: what to capture from agent traces, tool calls and knowledge retrieval, how it lands in Elasticsearch, and how it feeds evaluation, dashboards and the feedback loop. Partner with the data science team on evaluation strategy: golden datasets, evaluators to gate on quality, latency and cost. 10+ years of software engineering experience, with the recent years spent shipping and operating AI-driven products on real production traffic,



ideally products with public APIs and data models that had to evolve without breaking customers.

Familiarity with MCP, including exposing public MCP servers and tools.

Experience designing telemetry for AI systems, and using it to make engineering and product decisions.

Experience building products with public APIs and evolving data models, and the judgement that comes with maintaining external contracts as a product changes. Strong backend engineering skills in either Python or TypeScript: APIs, stateful workflows, data pipelines and production services. Comfort working with data scientists, engineers, and product managers as peers, translating between measurement and shipping, and communicating trade-offs clearly.

Practical

Elasticsearch experience. Health coverage for you and your family in many locations Increase your impact - We match up to $2000 (or local currency equivalent) for financial donations and service Up to 40 hours each year to use toward volunteer projects you love Qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex, pregnancy, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, disability status, or any other basis protected by federal, state or local law, ordinance or regulation. Elasticsearch develops and distributes technology and information that is subject to U.Belarus, Cuba, Iran, North Korea, Syria, or Russia, including the Ukrainian territories annexed by Russia (The Crimea region of Ukraine, The Donetsk People's Republic (DNR), The Luhansk People's Republic (LNR), Kherson or Zaporizhzhia).

Qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex, pregnancy, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, disability status, or any other basis protected by federal, state or local law, ordinance or regulation.

📌 Principal Ai Engineer - Context - Agents And Context (Cataluña)
🏢 Elastic
📍 Cataluña