# Principal Agentic AI Security Engineer

**Company**: Hewlett Packard Enterprise
**Location**: Spring, Texas
**Work arrangement**: hybrid
**Experience**: senior
**Job type**: full-time
**Salary**: Annual Salary USD 132,500 - 252,500 in Colorado // 143,000 - 290,500 in California // 126,500 - 290,500 in Georgia & North Carolina & Texas
**Category**: Engineering
**Industry**: Technology

**Apply**: https://hpe.wd5.myworkdayjobs.com/en-US/Jobsathpe/job/Spring-Texas-United-States-of-America/Principal-Agentic-AI-Security-Engineer_1218095-2?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_0dab3cbf-af8

## Description

Hewlett Packard Enterprise is seeking a Principal Agentic AI Security Engineer to design, build, and operate production-grade agentic systems that combine foundation models, software services, enterprise data, tools, and automation.

The role focuses on system architecture, agent orchestration, model-agnostic AI integration, deterministic execution, and the engineering of secure and reliable platforms for complex multi-step workflows.

Responsibilities:

- Design and develop scalable architectures for production-grade agentic AI systems.

- Build agent orchestration, multi-agent workflows, state management, memory, tool integration, and human-in-the-loop capabilities.

- Design reusable execution harnesses and services that separate AI reasoning and planning from deterministic execution.

- Develop model-agnostic interfaces supporting multiple foundation models, providers, and inference platforms.

- Build and integrate MCP servers, APIs, tool registries, skills, enterprise services, and data sources.

- Develop retrieval and context services including RAG, hybrid search, vector databases, and agent memory.

- Build backend services supporting asynchronous and distributed agent execution.

- Design evaluation and testing capabilities for agent behavior, tool usage, task completion, security, reliability, and performance.

- Implement observability across agent execution, model interactions, tools, state transitions, and system performance.

- Apply security engineering principles including least privilege, sandboxing, authorization, secrets management, guardrails, and auditability.

- Deploy and operate agentic services using containers, Kubernetes, CI/CD, and modern cloud-native engineering practices.

- Evaluate emerging models, frameworks, protocols, and technologies while maintaining architectural independence from individual vendors or platforms.

Education and Experience Required:

- Bachelor's or Master's degree in Computer Science, Engineering, Artificial Intelligence, or a related technical discipline, or equivalent practical experience.

- Typically 5–8 years of software engineering, platform engineering, distributed systems, AI engineering, or related experience.

- Demonstrated experience designing and delivering production software systems.

- Hands-on experience developing LLM-powered or agentic systems strongly preferred.

Knowledge and Skills:

- Agentic AI engineering requires knowledge across multiple technical disciplines. Successful candidates should demonstrate deep expertise in at least two of the five concentration areas below and strong working knowledge across the remaining areas.

Concentration Areas:

- System Design & Architecture

- Agentic Systems & Harness Engineering

- Model-Agnostic AI & Context Engineering

- Platform Engineering & Production Reliability

- Evaluation, Security & AI Safety

Additional Preferred Skills:

- Experience building reusable agent platforms, harnesses, or tool ecosystems.

- Experience with cybersecurity automation or security-sensitive systems.

- Experience operating open-weight models and commercial foundation-model platforms.

- Experience with enterprise-scale distributed or cloud-native systems.

- Ability to communicate system architecture, technical tradeoffs, and design decisions clearly.

Benefits:

- Comprehensive suite of benefits that supports physical, financial, and emotional wellbeing.

- Investment in career development and growth.

- Unconditional inclusion and celebration of individual uniqueness.

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## Skills

### Required
- Agentic AI engineering
- System Design & Architecture
- Agentic Systems & Harness Engineering
- Model-Agnostic AI & Context Engineering
- Platform Engineering & Production Reliability
- Evaluation, Security & AI Safety
- Python
- backend software engineering
- REST/gRPC APIs
- asynchronous services
- messaging
- distributed processing
- Docker
- Kubernetes
- CI/CD
- cloud infrastructure

### Nice to have
- Experience building reusable agent platforms, harnesses, or tool ecosystems
- Experience with cybersecurity automation or security-sensitive systems
- Experience operating open-weight models and commercial foundation-model platforms
- Experience with enterprise-scale distributed or cloud-native systems
- Ability to communicate system architecture, technical tradeoffs, and design decisions clearly

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Source: [Apply at hpe.wd5.myworkdayjobs.com](https://hpe.wd5.myworkdayjobs.com/en-US/Jobsathpe/job/Spring-Texas-United-States-of-America/Principal-Agentic-AI-Security-Engineer_1218095-2?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)