Principal AI Engineer (Context, Agents and Context)

Join Elastic as a Principal AI Engineer, where you'll lead the improvement loop for the Context Engine, a key component of our AI-driven products. You'll work at the intersection of engineering, data science, and product, writing production code, designing evaluation and telemetry, and setting the technical bar for agentic behavior. This hybrid role offers flexible location and schedule, fully paid health coverage, generous vacation days, and more.

• Posséder le cycle d'amélioration de la production pour le moteur de contexte, en comprenant comment les automatisations d'extraction, les outils de récupération et la mémoire se comportent.
• Définir comment nous itérons sur les agents et les compétences en toute sécurité : versionnage et déploiement des invites, des compétences et des automatisations.
• Concevoir la télémétrie dont nous avons besoin pour prendre des décisions d'ingénierie éclairées.

• Direct experience building agents with state and memory, and iterating on prompts, skills and tool behaviour safely in production
• Comfort working with data scientists, engineers, and product managers as peers, translating between measurement and shipping, and communicating trade-offs clearly
• 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
• A pragmatic, low-ego style suited to a distributed, async-first team
• A track record of eval-driven product improvement: you have diagnosed agent or LLM behaviour from traces and user feedback, designed the evaluation that exposed the problem, shipped the fix and measured the outcome
• Experience building products with public APIs and evolving data models, and the judgement that comes with maintaining external contracts as a product changes
• Familiarity with MCP, including exposing public MCP servers and tools
• Experience running product experiments end to end: instrumentation, unattended execution, and interpreting results
• Strong backend engineering skills in either Python or TypeScript: APIs, stateful workflows, data pipelines and production services
• Experience designing telemetry for AI systems, and using it to make engineering and product decisions
• Experience with agent frameworks such as LangGraph, CrewAI, Claude Agent SDK, or similar
• Agentic retrieval experience, including knowledge representation
• Practical Elasticsearch experience