Una candidatura completa en un minuto
Currículum y carta de presentación personalizados, listos para enviar.
Hewlett Packard Enterprise (HPE) is hiring a Senior Application Security Engineer for a remote position. You will shape secure SDLC, implement CI/CD security controls, and lead AI/LLM security initiatives across engineering teams.
You will collaborate with architecture, DevOps, and software teams to embed security by default and drive measurable risk reduction. Responsibilities include designing guardrails for secure pipelines, enabling vulnerability prioritization, and delivering automated
This role has been designated as 'Remote/Teleworker', which means you will primarily work from home. 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.
Are you ready to make an impact at one of the world's leading technology companies? HPE's Cybersecurity team is where you can do just that. We're looking for a dynamic and experienced Application Security Engineer to join our team. If you're passionate about shaping the future of cybersecurity and ready for your next challenge, we'd love to hear from you.
We are hiring an Application Security Engineer to build how our enterprise secures software, from first commit to production. This is not a role for running scans and filing tickets. You will design the guardrails, automation, and AI-powered tooling that let engineering teams ship securely by default, and you will prove they work with data. You will work as a peer to engineering, architecture, and DevOps leaders and own outcomes across secure SDLC, CI/CD and supply chain integrity, WAF/WAAP and API protection, and AI/LLM security. The right person sees a recurring problem and builds the capability that makes it go away.
Build security into the SDLC as paved roads, so the secure path is the easiest path for every engineering team. Define the secure coding standards and reference patterns that teams across the enterprise build against. Build the vulnerability prioritization capability that shows where real risk sits across code, pipelines, and deployed services, and drive remediation to measurable closure. Establish a threat modeling practice for applications, APIs, and delivery pipelines that scale beyond a single team.
Architect the security control layer for our CI/CD platforms (GitHub Actions, Jenkins, GitLab, Azure DevOps) so every pipeline inherits it by default. Design the automated testing pipeline that runs SAST, DAST, SCA, and container scanning on every build, tuned for signal over noise. Build the automation that keeps our attack surface visible: API discovery, dependency scanning, SBOM generation, and secrets detection.
Build reusable AI agent skills and workflows inside CI/CD (e.g., agentic coding tools, MCP-based integrations) that review every pull request for insecure patterns, authN/authZ gaps, secrets exposure, and risky dependency changes, and deliver CWE/OWASP-mapped findings developers can act on. Build AI-driven security testing that generates targeted test cases (API abuse cases, fuzzing inputs, prompt-injection and jailbreak suites), triages SAST/SCA/DAST results to cut false positives and proposes remediation PRs for human review. Define the guardrails AI agents operate under our pipelines: least-privilege tokens, human-in-the-loop approval, output-accuracy evaluation, and audit logging. Build the AI-specific scanning capability that catches insecure LLM orchestration patterns before they ship. Establish a reusable threat modeling approach for RAG architectures and autonomous agents. Define the framework for secure AI adoption in enterprise applications, covering data security, access controls, model input/output handling, and misuse prevention. Familiarity with agentic AI frameworks such as LangGraph and similar orchestration frameworks
Demonstrated ability to drive initiatives end-to-end, taking ownership of tasks, deliverables, and outcomes. Shape product, platform, and DevOps roadmaps as trusted advisors, translating technical risk into business decisions. Choose, implement, and prove the tooling that closes the gaps we have today, with metrics that show the impact. Grow security capability inside engineering teams through mentoring secure coding and pipeline practices. Help scale the Security Champions program into a self-sustaining network.
6+ years in Application Security, Product Security, or Secure Software Development, with a track record of building capabilities, not only operating them. Has designed security controls for CI/CD pipelines and source repositories (GitHub, GitLab, Jenkins, or similar) at scale. Has built and tuned SAST, DAST, SCA, and container