AI​/ML Engineer - Agentic

AI/ML Engineer - Agentic

This hybrid role expects you to work approximately 2 days per week from an HPE office. The AI/ML Engineer – Agentic is a senior individual contributor responsible for designing, building, and operating a production‑grade agentic orchestration platform, including multi‑agent workflows and MCP server‑based tool infrastructure. The focus is on enterprise‑scale LLM integration, shared retrieval and memory services, and high‑performance backend systems that power agent execution.

• Design, build, and own a production‑grade agentic orchestration platform, implementing scalable multi‑agent workflows using frameworks such as Lang Graph or equivalent.
• Architect, develop, and operate the MCP server infrastructure, including inter‑agent communication, tool/server registries, domain isolation, versioning, and lifecycle management.
• Integrate and operate LLM services at enterprise scale, supporting streaming, structured outputs, tool/function calling, and robust error handling across agent workflows.
• Build and maintain retrieval and memory services for agentic systems, including RAG pipelines, Open Search‑backed vector stores, hybrid search, and relevance optimization.
• Develop and operate high‑performance backend services (FastAPI, gRPC, async systems, messaging) that power orchestration, tool execution, and agent runtime behavior.
• Own observability and reliability for non‑deterministic systems, delivering end‑to‑end tracing, monitoring, and cost/performance visibility for agent executions.
• Manage cloud‑native infrastructure and deployment, including Kubernetes workloads, containerised services, CI/CD pipelines, and resource optimisation (CPU/memory, autoscaling).

Bachelor’s degree in computer science, engineering, information systems, or a closely related quantitative discipline. Master’s degree is desirable. Typically 4‑7 years of experience in relevant technical roles.

• Production experience with agentic frameworks:
  Lang Graph (preferred), Claude Agent SDK, or equivalent.
• Deep understanding of multi‑agent architectures: supervisor/worker patterns, hierarchical agent graphs, ReAct loops, ReWoo.
• Hands‑on with inter‑agent communication protocols: MCP (Model Context Protocol), A2A, tool registry / server registry.
• LLM & ML Engineering: LLM API integration at scale, structured outputs, streaming, function/tool calling, error handling.
• RAG pipeline design and optimisation: chunking strategies, re‑ranking, hybrid search, tuning of retrieval knobs.
• Vector store experience:
  Open Search or equivalent.
• Applied ML intuition: fine‑tuning concepts, prompt engineering, evaluations, QLoRA, PEFT.
• Backend development:
  FastAPI, gRPC, Kafka, Redis, message queues, async system design.
• API design:
  GraphQL and/or REST at enterprise scale.
• Observability and monitoring for non‑deterministic systems:
  Lang Fuse, Prometheus, or equivalent.
• Kubernetes: deploying, scaling, and managing workloads (Deployments, Services, Config Maps, Secrets).
• Container image management: building, tagging, versioning, and pushing images via Docker; familiarity with ECR, GCR, Docker Hub.
• CI/CD pipelines for automated build and deploy (Git Hub Actions, Jenkins, ArgoCD, or similar).
• Resource management: CPU/memory limits, autoscaling (HPA/VPA), health probes.
• Additional preferred skills: multi‑tenant architecture awareness (rate limiting, auth, tenant isolation), knowledge base and cost optimisation experience (AWS Bedrock, Open Search Serverless).

Annual Salary: USD 136, (California, U.S.).

Hewlett Packard Enterprise is an Equal Employment Opportunity/ Veterans/Disabled/LGBT employer. We do not discriminate on the basis of race, gender, or any other protected category, and all decisions we make are based on qualifications, merit, and business need.