Agentic AI Engineer

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale. 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. Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI.

The Elastic IT team is moving beyond simple chat to the next frontier: Agentic Workflows and Agent-to-Agent (A2A) Systems. As an Agentic AI Engineer, you will build multi-agent ecosystems that are self-directed, collaborate, delegate tasks, and execute complex business processes across the organization. You will focus on large language models (LLMs), agent orchestration, and A2A integration frameworks to power our intelligent workforce.

• Design, build, and deploy agent-to-agent (A2A) communication architectures and workflows that enable autonomous agents to collaborate, delegate tasks, and negotiate multi-step business processes.
• Integrate advanced LLMs, both proprietary and open-source, with enterprise APIs using tool-calling methods, and connect with third-party SaaS applications.
• Use advanced Retrieval-Augmented Generation (RAG) techniques, implementing strategies that connect enterprise context using search and vector storage engines.
• Provision and manage robust cloud environments (AWS, Azure, GCP) using Terraform to support high-concurrency demands of LLM inferences and multi-agent coordination.
• Support modern DevOps practices, including creating CI/CD pipelines for automated testing, deployment, and versioning, and evaluate LLMs and agentic workflows regularly.
• Apply strict security and network fundamentals (VPC configurations, secure API gateways, encryption, and IAM controls) to secure inter-agent communication.
• Create systems to monitor how multiple agents interact, check model accuracy, manage token spending, and identify model drift or agent loops.
• Keep detailed technical documents for LLM integration protocols, A2A interaction flows, and cloud infrastructure deployments.

• 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.
• 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.
• 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, AutoGen, etc., along with tracing platforms like LangSmith.
• Strong understanding of emerging AI interoperability standards, such as the Model Context Protocol (MCP) and open multi-agent communication specifications.
• Contribute production code using ReactJS / NodeJS/Java/Spring, Kotlin Multiplatform SDK and its native layers, Angular/TypeScript Portal and JavaScript Web SDK, NoSQL data modeling, streaming and messaging/queueing technologies.
• Practical knowledge of RAG patterns, vector databases, hybrid search architectures, and context management strategies.
• Hands-on experience with DevOps practices and infrastructure automation using Terraform, Docker, and Kubernetes for scalable AI deployments.
• Strong knowledge of secure cloud architectures, zero-trust network design, private endpoints, and identity management (OAuth, SAML, IAM) for secure A2A interactions.
• Experience setting up observability frameworks (logging, distributed tracing, and metrics) to track non-deterministic multi-agent workflows, token costs, and LLM output quality.
• Knowledge of the broader agentic and workflow landscape (e.g., Workday A2A, Salesforce Agentforce, ServiceNow AI Agents).

Elastic is a distributed company with a focus on diversity and inclusion. They offer competitive pay based on the work you do, health coverage for you and your family in many locations, flexible locations and schedules for many roles, generous vacation days, a match up to $2000 for financial donations and service, up to 40 hours each year for volunteer projects, and a minimum of 16 weeks of parental leave. Elastic is an equal opportunity employer.