Agentic AI Engineer

Elastic is hiring an Agentic AI Engineer in Bangalore.

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. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. 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 organization

Requirements

• Experience with AI-assisted development, code review, test generation, working through unfamiliar code, drafting specifications, summarizing incidents, and accelerating research.

• Experience in shipping features covering full stack from design, build, test and deploy across the stack from database and portal through APIs, backend services, and the data pipeline

- LLM & GenAI Expertise: Deep experience integrating, fine-tuning, and optimizing foundation models (e.g., OpenAI, Anthropic, open-source models), including expertise in prompt engineering, tool calling, and structured outputs.

- Agent-to-Agent (A2A) Protocols: Proven success building multi-agent systems, inter-agent messaging pipelines, state management frameworks, and dynamic task delegation protocols.

- Agentic Frameworks: Hands-on experience with multi-agent orchestration frameworks such as LangGraph, LangChain, AutoGen, etc. along with tracing platforms like LangSmith.

- Market Trends & Interoperability: Strong understanding of emerging AI interoperability standards, such as the Model Context Protocol (MCP) and open multi-agent communication specifications.

- Programming: Contribute production code to our product code base using ReactJS / NodeJS/Java/Spring, our Kotlin Multiplatform SDK and its native layers, Angular/TypeScript Portal and JavaScript Web SDK, NoSQL data modeling, streaming and messaging/queueing technologies.

- Enterprise Grounding & Vector Search: Practical knowledge of RAG patterns, vector databases, hybrid search architectures, and context management strategies.

- DevOps & Infrastructure as Code (IaC): Hands-on experience with DevOps practices and infrastructure automation using Terraform, Docker, and Kubernetes for scalable AI deployments.

About Elastic

See the company's official careers page for full details, then apply using the button below.