Lead Agentic AI Offensive Security Engineer
About The Position
Hewlett Packard Enterprise’s Cybersecurity team is seeking a Lead Agentic AI Engineer to design, enhance, and support the technical direction of its AI-enabled offensive security organization. The role architects and delivers secure, reliable, production-grade agentic AI platforms that accelerate and scale cybersecurity triage, investigation, detection engineering, response, and other complex workflows. The position owns reference architecture and engineering standards for production agentic AI systems. It leads the design of reusable agent execution harnesses, multi-agent workflows, model-agnostic interfaces, retrieval and memory services, enterprise integrations, and practices for evaluation, observability, reliability, security, and AI safety. The role also leads cross-functional architecture decisions, mentors engineers, and communicates technical tradeoffs to senior leadership. The role is hybrid, requiring an average of two days per week in an HPE office.
Requirements
- Demonstrated deep expertise in at least three of these 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.
- 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 an 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.
Nice To Haves
- Experience with cybersecurity automation, security operations, offensive security, adversary simulation, reusable agent platforms, or open-weight inference.
- Experience with frameworks such as OWASP Top 10 for LLM Applications, MITRE ATLAS, MITRE ATT&CK, or NIST AI RMF.
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 for 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.
Benefits
- A comprehensive suite of benefits supporting physical, financial, and emotional wellbeing.
- Career development programs to help employees pursue career goals and develop expertise.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
