Lead Agentic AI Offensive Security Engineer
Hewlett Packard Enterprise is hiring a Lead Agentic AI Offensive Security Engineer. Level rates it ; you can apply on Hewlett Packard Enterprise.
Level's read on this job
- Level rates this cybersecurity role Builds AI ●●●●: the job is building AI systems.
- Tools and skills the posting cites include Claude, LangGraph and AutoGen.
- Level classifies it as a lead role.
- Level lists 1,700+ other open roles at Hewlett Packard Enterprise.
- The role was posted in the last few days.
AI in this role
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, structured generation, and function calling.
- Expert Python and backend engineering skills, including REST/gRPC, messaging, Docker, Kubernetes, CI/CD, and cloud infrastructure.
- Practical experience with agent evaluation, trajectory and regression testing, AI security, and production reliability.
Accessibility
HPE is committed to creating an inclusive and accessible workplace and encourages applications from all qualified individuals, including those with disabilities. If you believe you require accommodation during any stage of the application or interview process, please submit your request by completing our secure form linked here.
Note: This option is reserved for applicants needing assistance/reasonable accommodation related to a disability.
What We Can Offer You:
Health & Wellbeing
We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.
Personal & Professional Development
We also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have — whether you want to become a knowledge expert in your field or apply your skills to another division.
Unconditional Inclusion
We are unconditionally inclusive in the way we work and celebrate individual uniqueness. 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.
Let's Stay Connected:
Follow @HPECareers on Instagram to see the latest on people, culture and tech at HPE.
Job:
Information TechnologyJob Level:
TCP_07The expected salary/wage range for this position is provided below. Actual offer may vary from this range based upon geographic location, work experience, education/training, and/or skill level.
– United States of America: Annual Salary USD 183,000 - 365,000 in Colorado // 197,000 - 395,000 in Massachusetts // 197,000 - 420,000 in California // 173,000 - 420,000 in North Carolina & Texas
The listed salary range reflects base salary. Variable incentives may also be offered.
Information about employee benefits offered in the US can be found at https://myhperewards.com/main/new-hire-enrollment.html
The estimated job application period closure is February 1 2027; this timeline is provided for transparency and internal planning purposes.HPE 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 made on the basis of qualifications, merit, and business need. Our goal is to be one global team that is representative of our customers, in an inclusive environment where we can continue to innovate and grow together. Please click here: Equal Employment Opportunity.
Hewlett Packard Enterprise is EEO Protected Veteran/ Individual with Disabilities.
HPE will comply with all applicable laws related to employer use of arrest and conviction records, including laws requiring employers to consider for employment qualified applicants with criminal histories.
Recruitment Fraud Alert
We have become aware of an increase in fraudulent recruitment activities in which individuals impersonate our company or authorized recruitment agencies to offer fake employment opportunities. These scams may occur through false websites, emails, social media, or chat-based applications and often aim to obtain personal information or money. Please note that Hewlett Packard Enterprise (HPE), its direct and indirect subsidiaries and affiliated companies, and its authorized recruitment agencies/vendors will never charge a candidate a registration fee, hiring fee, or any other fee in connection with its recruitment and hiring process. We also never request personal information such as back account details, Social Security numbers, or national IDs via social media or chat applications.
All legitimate job opportunities will come through official company channels, and candidates are responsible for verifying the credentials of any third party claiming to represent the company. Any reliance on fraudulent communication is at the individual’s own risk, and HPE disclaims legal liability for any resulting damages. If you suspect recruitment fraud, do not share personal information or make any payments and report the incident to your local authorities immediately.
How we rate this
Lead Agentic AI Offensive Security Engineer at Hewlett Packard Enterprise rates 89 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in cybersecurity jobs at this level
Pay
- Typical cybersecurity job
- $160k
This posting doesn't list pay. Use the typical cybersecurity figure when pay comes up. See cybersecurity jobs
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you think about the risk of an AI system in this kind of role failing silently?
- What are the limits of Claude that you've run into, and how did you work around them?
- What's a project where you used LangGraph hands-on?
- Walk me through how you've used AutoGen in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: RAG, AI Safety, Claude, LangGraph, and AutoGen. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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