Jobs / United States / Hewlett Packard Enterprise Company

Hewlett Packard Enterprise Company

Lead Agentic AI Offensive Security Engineer

6 Locations Posted today

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Skills this job asks for

CybersecurityTriageLeadershipLLMsMicroservicesPythonDockerKubernetesCI/CD

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Sponsorship verdict

Sponsorship possible

One solid signal, not two. Worth applying, and worth asking about sponsorship early.

  • Employer is on a government sponsor recordThe US Department of Labor certified 486 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first.
  • The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
  • No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area.
  • What Hewlett Packard Enterprise Company paid sponsored hires in similar roles3 certified filings for “Senior AI and Machine Learning Engineer” (Data Scientists) in CA: $124k–$228k, median $174k.
  • Confirmed live todayWhen a source last listed this job as open.
Details and sources
Employer is on a government sponsor record
The US Department of Labor certified 486 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. Source: LCA disclosure data (US Department of Labor (OFLC)).
No salary bar for this route
H-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
What Hewlett Packard Enterprise Company paid sponsored hires in similar roles
3 certified filings for “Senior AI and Machine Learning Engineer” (Data Scientists) in CA: $124k–$228k, median $174k. Most were filed at wage level I (50%) — 1 lottery entry, ≈15% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).

US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).

A verdict summarises public evidence. It is not legal advice and never a guarantee: the employer and the immigration authority decide. Sign in to factor in where you can already work.

About the role

Lead Agentic AI Offensive Security Engineer    This role has been designed as 'Hybrid' with a requirement that you will work on average 2 days per week from an HPE office. Who We Are: Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today’s complex world. Our culture thrives on finding new and better ways to accelerate what’s next. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE. Job Description: HPE’s Cybersecurity team is seeking a Lead Agentic AI Engineer to design, enhance and support  the technical direction of our AI-Enabled Offensive  security organization. Using your expertise in offensive security, you will architect and deliver secure, reliable, production-grade agentic AI platforms. These platforms will accelerate and scale cybersecurity triage, investigation, detection engineering, response, and other complex workflows. Primary 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 commercial, cloud-hosted, and open-weight models, including routing, fallback, and workload-based selection. • Architect retrieval, context, and memory services using technologies such as 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 least privilege, sandboxing, authorization, secrets management, guardrails, auditability, and defenses against prompt injection, tool abuse, and data leakage. • Lead cross-functional architecture decisions, mentor engineers, and communicate technical tradeoffs to senior leadership. Experience and Skills • Candidates should demonstrate deep expertise in at least three areas, with Agentic Systems & Harness Engineering required: • System Design & Architecture • Agentic Systems & Harness Engineering • Model-Agnostic AI & Context Engineering • Platform Engineering & Production Reliability • Evaluation, Security & AI Safety • Experience with cybersecurity automation, security operations, offensive security, adversary simulation, reusable agent platforms, open-weight inference, or frameworks such as OWASP Top 10 for LLM Applications, MITRE ATLAS, MITRE ATT&CK, and NIST AI RMF is preferred. • 10+ years of experience in software, platform, distributed-systems, or AI engineering, with demonstrated technical leadership on production systems. • Proven experience architecting and operating production LLM-powered or agentic systems across their full lifecycle. • Deep expertise in distributed systems, microservices, APIs, event-driven architectures, workflow and state management, scalability, concurrency, and fault tolerance. • Strong hands-on experience with agent orchestration, planning, tool calling, delegation, memory, and long-running workflows using LangGraph, Claude Agent SDK, Semantic Kernel, AutoGen, or equivalent. • Experience with foundation-model APIs and open-weight or self-hosted models,

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