Agentic AI Engineer

About this job

The Agentic AI Engineer role at Elastic in Bangalore involves joining the Elastic IT team to transition beyond simple chat systems into advanced Agentic Workflows and Agent-to-Agent (A2A) Systems. Elastic is the Search AI Company, providing cloud-based search, security, and observability solutions used by major enterprises to accelerate results using structured and unstructured data. In this role, you will build self-directed multi-agent ecosystems where autonomous agents collaborate, delegate tasks, and execute complex business processes across the organization. A normal day involves designing A2A communication architectures, integrating large language models with enterprise APIs, implementing retrieval-augmented generation techniques, provisioning cloud environments, and monitoring multi-agent interactions to ensure optimal performance, security, and accuracy.

Responsibilities

• Design and deploy A2A communication architectures and workflows for autonomous agent collaboration.
• Integrate advanced LLMs with enterprise APIs using tool-calling methods and third-party SaaS apps.
• Implement advanced RAG techniques using search and vector storage engines for enterprise grounding.
• Provision and manage cloud environments across AWS, Azure, and GCP using Terraform.
• Support modern DevOps practices through CI/CD pipelines for automated testing, deployment, and versioning.
• Apply security and network fundamentals to secure inter-agent communication and protect data.
• Create monitoring systems to track multi-agent interactions, model accuracy, and token spending.

Requirements

• Deep experience integrating, fine-tuning, and optimizing foundation models with prompt engineering.
• Proven success building multi-agent systems, inter-agent messaging pipelines, and task delegation protocols.
• Hands-on experience with orchestration frameworks like LangGraph, LangChain, and AutoGen.
• Advanced proficiency in Python or TypeScript for backend orchestration and API service development.
• Practical knowledge of RAG patterns, vector databases, and hybrid search architectures.
• Hands-on experience with DevOps practices and infrastructure automation using Terraform, Docker, and Kubernetes.
• Strong knowledge of secure cloud architectures, zero-trust network design, and IAM controls.

Good to have

• Strong understanding of emerging AI interoperability standards like Model Context Protocol.
• Experience setting up observability frameworks to track non-deterministic multi-agent workflows.
• Knowledge of enterprise AI platforms such as Workday A2A, Salesforce Agentforce, or ServiceNow AI Agents.

Who should apply

This role suits professionals with strong expertise in generative AI, large language models, and multi-agent orchestration frameworks who want to build next-generation enterprise systems. Candidates should have a background in Python or TypeScript, cloud infrastructure automation, and secure API integration. The company notes that age is just a number and explicitly welcomes applicants whether they are just out of college or more experienced, making this an opportunity open to a wide range of qualified background levels.

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