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Elastic

Searches enterprise data and monitors systems

Agentic AI Engineer

AI Application Engineering +1Posted on Nov 11
Full-timeBengaluru, Karnataka, IndiaNo salary listedIn-person

About the Job

Requirements

  • Experience using AI-assisted development for code review, test generation, unfamiliar-code investigation, specification drafting, incident summarization, and research.
  • Experience shipping full-stack features across design, build, test, and deployment, covering databases, portals, APIs, backend services, and data pipelines.
  • Deep experience integrating, fine-tuning, and optimizing foundation models, including OpenAI, Anthropic, or open-source models, prompt engineering, tool calling, and structured outputs.
  • Proven success building multi-agent systems, inter-agent messaging pipelines, state-management frameworks, and dynamic task-delegation protocols.
  • Hands-on experience with multi-agent orchestration frameworks such as LangGraph, LangChain, and AutoGen, and tracing platforms such as LangSmith.
  • Strong understanding of AI interoperability standards such as the Model Context Protocol and open multi-agent communication specifications.
  • Ability to contribute production code using ReactJS, NodeJS, Java, Spring, Kotlin Multiplatform SDK and native layers, Angular, TypeScript, JavaScript Web SDK, NoSQL data modeling, and streaming and messaging/queueing technologies.
  • Practical knowledge of retrieval-augmented generation patterns, vector databases, hybrid search architectures, and context-management strategies.
  • Hands-on experience with DevOps practices and infrastructure automation using Terraform, Docker, and Kubernetes.
  • Strong knowledge of secure cloud architectures, zero-trust network design, private endpoints, and identity management with OAuth, SAML, and IAM.
  • Experience establishing observability frameworks using logging, distributed tracing, and metrics to track multi-agent workflows, token costs, and LLM output quality.
  • Knowledge of enterprise AI platforms and workflows, including Workday A2A, Salesforce Agentforce, and ServiceNow AI Agents.

Responsibilities

  • Design, build, and deploy agent-to-agent communication architectures and workflows that let autonomous agents collaborate, delegate tasks, and negotiate multi-step business processes.
  • Integrate proprietary and open-source large language models with enterprise APIs using tool-calling methods, and connect third-party SaaS applications.
  • Implement retrieval-augmented generation strategies that ground enterprise context using search and vector-storage engines to improve accuracy and reliability of inter-agent operations.
  • Provision and manage cloud environments on AWS, Azure, or GCP using Terraform to support high-concurrency LLM inference and multi-agent coordination.
  • Create CI/CD pipelines for automated testing, deployment, and versioning, and regularly evaluate LLMs and agentic workflows.
  • Secure inter-agent communication and sensitive enterprise data using VPC configurations, secure API gateways, encryption, and IAM controls.
  • Create monitoring systems for multi-agent interactions to assess model accuracy, manage token spending, and identify model drift or agent loops.
  • Maintain technical documentation for LLM integration protocols, A2A interaction flows, and cloud infrastructure deployments.

About the Company

Elastic

Searches enterprise data and monitors systems

Elastic builds search, observability and security software for developers, IT operations teams and security analysts. Elasticsearch indexes enterprise data so applications can retrieve records, while Kibana gives teams dashboards for exploring results and investigating system activity. Customers use the tools to search business information, monitor applications and infrastructure, and investigate threats across their data. Elastic sells managed cloud services and self-managed subscriptions, with resource-based hosted pricing, usage-based serverless pricing and licenses tied to nodes and memory. Founded in 2012, Elastic lists San Francisco, California, as its headquarters.

Company size
1,001-5,000
Company stage
IPO
Headquarters
San Francisco, CA
Founded
2012

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