Elastic AI Engineer

About the role

Join Elastic, a leading company in the field of search and data analytics. As an Elastic AI Engineer, you will be at the forefront of developing autonomous, enterprise-grounded agents that enhance productivity across the organization. You will be responsible for designing and implementing sophisticated agentic workflows, ensuring agents are grounded in enterprise knowledge, integrating AI models and tools, and overseeing the lifecycle management of agents. This role requires a strong background in AI, programming, cloud environments, and the Elastic Stack. Enjoy a flexible work environment, comprehensive health coverage, generous vacation days, and opportunities for charitable giving. Key missions: Invent and implement sophisticated agentic workflows that use reasoning and tools to complete end-to-end business processes.. Develop and fine-tune LLMs and integrate them with internal APIs and third-party SaaS tools to enable autonomous action.. Oversee the training, deployment, and performance optimization of agents, ensuring they remain secure, reliable, and compliant. Profile: - Proven success in delivering independent GenAI projects, specifically those involving autonomous task completion or complex workflow automation - Programming: Experience with Python or TypeScript for backend logic and agent orchestration - Cloud & Orchestration: Familiarity with Kubernetes (Operators/Controllers), Docker, and Terraform for automated deployment - 3-5 years of work experience in a relevant field - Expertise in Enterprise Agentic & Workflow Platforms: Deep familiarity with leading agentic AI and workflow automation platforms (such as Microsoft Copilot Studio, Salesforce Agentforce, ServiceNow AI Agents.) - Agentic Frameworks: Familiarity with LangGraph, LangChain, and LangSmith for building and debugging multi-agent systems - Knowledge of Elasticsearch Relevance Engine (ESRE), Jina AI, and advanced RAG patterns is critical - Market Trend Integration: Proven ability to apply emerging market trends—such as Multi-Agent Orchestration and Model Context Protocol (MCP)—to build high-impact, cost-optimized solutions that scale across the enterprise - Minimum 1 year experience building with the Elastic Stack - Model Expertise: Hands-on experience with LLM providers - Bachelor’s or Master’s degree in Computer Science or a related engineering field - Strong communication skills with the ability to translate business requirements into technical agent architectures - A commitment to Ethical AI and responsible development practices - Experience with containerization and orchestration (e.g., Docker, Kubernetes) - Knowledge of DevOps practices for model deployment and automation