Hybrid Lead Agentic AI Security Engineer

Hewlett Packard Enterprise; Durham (NC); Hybrid; USD 173,000 - 420,000; Full time

Job summary

Hewlett Packard Enterprise in North Carolina seeks a Lead Agentic AI Engineer to design and operate agentic AI platforms for secure, production-grade use. You will own reference architectures, lead multi-agent workflows, and collaborate with senior leaders to shape technical direction.

The role requires deep expertise in distributed systems, Python backend, and open-weight models, with hybrid work requiring office days. Competitive US salary ranges apply.

Qualifications

• 10+ years of experience in software, platform, distributed-systems, or AI engineering.

Responsibilities

• Own the reference architecture and engineering standards for production agentic AI systems.
• Design reusable agent execution harnesses that separate AI reasoning and planning from deterministic execution.
• Lead multi-agent workflows, state management, memory, tool calling, human-in-the-loop controls, and long-running processes.
• Define model-agnostic interfaces supporting various models, including routing, fallback, and workload-based selection.
• Architect retrieval, context, and memory services using RAG, hybrid search, and vector databases.
• Establish strategies for MCP servers, A2A protocols, APIs, tool registries, and enterprise integrations.
• Define evaluation, observability, reliability, and security practices, including guardrails and data leakage defenses.
• Lead cross-functional architecture decisions, mentor engineers, and communicate tradeoffs to senior leadership.

Skills

System Design

Agentic Systems

Context Engineering

Platform Engineering

Security & AI Safety

Tools

LangGraph

Claude Agent SDK

Semantic Kernel

AutoGen

REST API

Docker

Kubernetes

Job description

Hewlett Packard Enterprise in North Carolina seeks a Lead Agentic AI Engineer to design and operate agentic AI platforms for secure, production-grade use. You will own reference architectures, lead multi-agent workflows, and collaborate with senior leaders to shape technical direction.

The role requires deep expertise in distributed systems, Python backend, and open-weight models, with hybrid work requiring office days. Competitive US salary ranges apply.