Principal Agentic AI Security Engineer (Offensive)

Hewlett Packard Enterprise; Andover (MA); Hybrid; USD 197,000 - 395,000; Full time

Job summary

Hewlett Packard Enterprise (HPE) is seeking a Lead Agentic AI Engineer for its Cybersecurity team. The role focuses on designing and supporting agentic AI platforms to accelerate triage, investigation, and response workflows.

You will own architectures, build reusable agent harnesses, and guide cross-functional teams in delivering secure, production-grade AI systems using state-of-the-art models and tool ecosystems. This position is hybrid, with on-site collaboration two days per week.

Qualifications

• 10+ years of software, platform, distributed-systems, or AI engineering experience.
• Proven leadership on production systems and technical direction.
• Experience architecting production LLM-powered or agentic systems.
• Deep expertise in distributed systems, microservices, APIs, and fault tolerance.
• Hands-on experience with agent orchestration, tool calling, and memory.

Responsibilities

• Own reference architecture and engineering standards for production agentic AI systems.
• Design reusable agent execution harnesses separating reasoning from execution.
• Lead multi-agent workflows, memory, and long-running processes.
• Define model-agnostic interfaces for diverse deployment models and APIs.
• Mentor engineers and communicate tradeoffs to senior leadership.

Skills

Agentic Systems & Harness

System Design & Architecture

Model-Agnostic AI

Platform Engineering

AI Safety & Security

Tools

LangGraph

Claude Agent SDK

Semantic Kernel

AutoGen

Docker

Kubernetes

REST/gRPC

CI/CD

Job description

Hewlett Packard Enterprise (HPE) is seeking a Lead Agentic AI Engineer for its Cybersecurity team. The role focuses on designing and supporting agentic AI platforms to accelerate triage, investigation, and response workflows.

You will own architectures, build reusable agent harnesses, and guide cross-functional teams in delivering secure, production-grade AI systems using state-of-the-art models and tool ecosystems. This position is hybrid, with on-site collaboration two days per week.