Agentic AI Engineer
Core
Design, build, and deploy autonomous multi-agent ecosystems (A2A) that collaborate, delegate tasks, and execute complex business processes using LLMs.
Role type
Senior IC Agentic AI Engineer (Multi-Agent Systems)
Builds
Self-directed agent-to-agent workflows and intelligent workforce systems (via careerplan.io/jobs/8247206-agentic-ai-engineer-at-elastic)
Domain
Enterprise AI, Search, and Observability
Deliverable
production ML models
Required skills
LLM integration and fine-tuning, Agent-to-Agent (A2A) protocols, Multi-agent orchestration frameworks (LangGraph, LangChain, AutoGen), Python or TypeScript, RAG and vector search, Infrastructure as Code (Terraform, Docker, Kubernetes), Cloud security (VPC, IAM, OAuth, SAML), LLM observability and evaluation
Preferred skills
Model Context Protocol (MCP), Enterprise AI platform knowledge (Workday, Salesforce, ServiceNow)
Technologies
OpenAI, Anthropic, LangSmith, AWS, Azure, GCP, Terraform, Kubernetes
Responsibilities
Design A2A communication architectures and workflows; Integrate LLMs with enterprise APIs and third-party SaaS; Implement RAG strategies for enterprise grounding; Provision and manage cloud environments for high-concurrency LLM inferences; Create CI/CD pipelines for automated testing and deployment; Apply security controls to secure inter-agent communication; Build systems to monitor agent interactions, token costs, and model drift; Document technical protocols and infrastructure deployments
Seniority
Senior, hands-on IC
