Lead Agentic AI Offensive Security Engineer

Hewlett Packard Enterprise

. Own the reference architecture and engineering standards for production agentic AI systems .

Posted 11/5/2026full-timeUnited StatesSenior💰 $173,000 - $420,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates extensive expertise in architecting and operating production agentic AI systems, with a strong focus on distributed systems, microservices, and AI security practices. Proven ability to lead technical teams, mentor engineers, and communicate complex architectural decisions effectively.

Highest-signal resume keywords

10+ Years Experience In Software EngineeringExpert Python And Backend Engineering SkillsDeep Expertise In Distributed SystemsExperience With Agent Orchestration And PlanningProven Experience Architecting Production LLM-Powered Systems

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Agent OrchestrationMicroservicesAPIsEvent-Driven ArchitecturesWorkflow ManagementScalabilityConcurrencyFault ToleranceAI SecurityProduction Reliability

Soft Skills

Technical LeadershipMentoringCommunication

Tools & Technologies

LangGraphClaude Agent SDKSemantic KernelAutoGenREST/gRPCDockerKubernetesCI/CDCloud InfrastructureVector Databases

Industry Keywords

Agentic SystemsModel-Agnostic AICybersecurity AutomationOWASP Top 10MITRE ATT&CKNIST AI RMF

Tech Stack

Tools & technologies

CloudCyber SecurityDistributed SystemsDockerGRPCKubernetesMicroservicesPython

About the role

Key responsibilities & impact

Own the reference architecture and engineering standards for production agentic AI systems
Design reusable agent execution harnesses separating 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 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

Requirements

What you’ll need

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

Benefits

Comp & perks

Comprehensive health and wellbeing benefits supporting physical, financial and emotional wellbeing
Personal and professional development programs
Flexible work arrangements to manage work and personal needs
Inclusive workplace culture
Reasonable accommodation during the application or interview process for applicants with disabilities