Agentic AI Engineer

Summary

Elastic is a leading company in search AI technology, enabling businesses to harness their data effectively. They are seeking an Agentic AI Engineer to design and implement advanced workflows that enhance enterprise productivity through autonomous agents.

Responsibilities

• Design and implement sophisticated agentic workflows that use reasoning and tools to execute end-to-end business processes
• Utilize Retrieval Augmented Generation (RAG) and the Elasticsearch Relevance Engine (ESRE) to ensure agents are deeply grounded in enterprise knowledge for high-accuracy task completion
• Develop and fine-tune LLMs and integrate them with internal APIs and third-party SaaS tools to enable autonomous action
• Provision and manage robust cloud-based environments (AWS, Azure, Google Cloud Platform) using Terraform to support the high-concurrency demands of enterprise agents
• Establish modern DevOps practices (CI/CD pipelines) to oversee the automated deployment, testing, and performance optimization of agents, keeping our agentic pipelines reliable and secure
• Apply strict security and network fundamentals (e.g., VPC configurations, secure API gateways, encryption, and IAM controls) to protect sensitive data and ensure strict compliance
• Implement comprehensive observability and tracing systems to monitor agent behavior, track execution latency, manage token spend, and proactively detect model drift or failure
• Act as a subject matter expert on the Elastic Stack, making technical recommendations that push the boundaries of AI-driven productivity
• Maintain comprehensive documentation of AI workflows, cloud infrastructure, and deployment processes

Skills

• Proven success in delivering independent GenAI projects, specifically those involving autonomous task completion or complex workflow automation
• A strong desire to learn and become an expert in Elasticsearch Relevance Engine (ESRE), advanced RAG patterns, and the broader Elastic ecosystem (we will help you get there!)
• Familiarity with LangGraph, LangChain, and LangSmith for building and debugging multi-agent systems
• Hands-on experience with DevOps practices and infrastructure automation, leveraging Terraform as well as containerization and orchestration technologies like Docker and Kubernetes
• Strong knowledge of secure cloud architectures, private networking, firewalls, VPC peering, and secure identity management (OAuth, SAML, IAM)
• Experience setting up observability frameworks (logging, distributed tracing, and metrics) to monitor complex, non-deterministic multi-agent workflows and application health
• Familiarity with leading agentic AI and workflow automation platforms (such as Microsoft Copilot Studio, Salesforce Agentforce, ServiceNow AI Agents)
• 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
• Experience with Python or TypeScript for backend logic and agent orchestration
• Hands-on experience with LLM providers
• Bachelor's or Master's degree in Computer Science or a related engineering field
• Strong communication and problem solving skills with the ability to translate business requirements into technical agent architectures
• Ability to work and thrive in a dynamic and fast-paced environment
• A commitment to Ethical AI and responsible development practices

Qualifications

Must Haves

• Proven success in delivering independent GenAI projects, specifically those involving autonomous task completion or complex workflow automation
• A strong desire to learn and become an expert in Elasticsearch Relevance Engine (ESRE), advanced RAG patterns, and the broader Elastic ecosystem (we will help you get there!)
• Familiarity with LangGraph, LangChain, and LangSmith for building and debugging multi-agent systems
• Hands-on experience with DevOps practices and infrastructure automation, leveraging Terraform as well as containerization and orchestration technologies like Docker and Kubernetes
• Strong knowledge of secure cloud architectures, private networking, firewalls, VPC peering, and secure identity management (OAuth, SAML, IAM)
• Experience setting up observability frameworks (logging, distributed tracing, and metrics) to monitor complex, non-deterministic multi-agent workflows and application health
• Familiarity with leading agentic AI and workflow automation platforms (such as Microsoft Copilot Studio, Salesforce Agentforce, ServiceNow AI Agents)
• 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
• Experience with Python or TypeScript for backend logic and agent orchestration
• Hands-on experience with LLM providers
• Bachelor's or Master's degree in Computer Science or a related engineering field
• Strong communication and problem solving skills with the ability to translate business requirements into technical agent architectures
• Ability to work and thrive in a dynamic and fast-paced environment
• A commitment to Ethical AI and responsible development practices

Benefits

• This role does not have a variable compensation component.
• This role is currently eligible to participate in Elastic's stock program
• Company-matched 401k with dollar-for-dollar matching up to 6% of eligible earnings
• Health coverage for you and your family in many locations
• Ability to craft your calendar with flexible locations and schedules for many roles
• Generous number of vacation days each year
• We match up to $2000 (or local currency equivalent) for financial donations and service
• Up to 40 hours each year to use toward volunteer projects you love
• Embracing parenthood with minimum of 16 weeks of parental leave