Job Description Job Role:

Security & Agentic AI DevSecOps Engineer (Product Security)

Location:

Milpitas, CA (5 days work from office)

Job Description:

Role Overview As an AI Security & Agentic AI DevSecOps Engineer, you will act as a hands‑on technical authority responsible for designing and implementing fully automated security controls across the software and AI lifecycle. Your focus will be to ensure that every meaningful security decision is enforced through automation, not manual processes. You will embed security as code, policy as code, and continuous verification into modern software platforms and agentic AI systems, enabling secure innovation at scale across cloud, hybrid, and air‑gapped environments. Key Responsibilities AI Security & Agentic Systems (Automation‑First) Design and implement automated Agentic and AI security controlsfor agentic systems, including: Automated model access control, inference authorization, and rate limiting\nPolicy‑driven prompt/instruction validation and misuse detection\nAutomated enforcement of agent‑to‑agent authentication and authorization\nImplement continuous, automated threat modeling for: LLM pipelines\nAgent orchestration frameworks\nAI gateways and inference services\nBuild secure‑by‑default reference architectures where AI guardrails are enforced via: Configuration‑as‑code\nRuntime policy engines\nAutomated security testing pipelines\nCreate Plugins , Hooks and Skills using claude code and or Microsoft AI foundry DevSecOps & Secure SDLC (End‑to‑End Automation) Implement fully automated Secure SDLC pipelines, integrating: SAST, DAST, SCA, secrets detection, container scanning, and IaC scanning\nAI‑specific security testing (prompt injection, model misuse, data leakage)\nAutomated build and release policy enforcement (fail gates, conditional approvals)\nEnsure all security checks are: Triggered automatically via CI/CD and MLOps pipelines\nEnforced consistently across dev, test, and production\nAutomate security validation during: Design reviews (template‑driven controls)\nArchitecture reviews (reusable security patterns)\nPre‑release readiness checks

SBOM, AI

‑BOM & Supply Chain Automation Design and operate automated SBOM and AI‑BOM pipelines, including: Continuous generation of SBOMs for software, containers, firmware, and artifacts\nAutomated AI‑BOMs covering models, datasets, checkpoints, and training artifacts\nImplement automated vulnerability, license, and provenance analysis: Continuous ingestion of CVEs and advisories\nAutomated policy enforcement for non‑compliant components\nIntegrate SBOM and AI‑BOM outputs into: CI/CD pipelines\nDeployment gates\nAudit and compliance reporting workflows Runtime Security, Risk & Metrics Automation Implement continuous, automated security monitoringacross: Application runtimes\nAI/ML inference services\nAgent workflows and interactions\nDevelop automated security metrics and telemetry to measure: Vulnerability exposure and remediation velocity\nSecure SDLC and DevSecOps maturity\nModel and AI risk posture over time\nAutomate security feedback loops so findings: Generate actionable tasks\nFeed directly into engineering backlogs\nDrive measurable risk reduction Technical Influence & Enablement Ability and willing to learn,teach and develop agentic AI workflow automation using copilot studio and or Claude code\nAct as a technical authority on AI security automation and DevSecOps.\nDefine reusable security automation patterns, templates, and reference implementations.\nPartner with engineering, AI/ML, platform, and compliance teams to replace manual security workflows with automated controls.\nContribute to internal security standards that mandate automation by default. Strong hands‑on experience designing automated Product Security or AI Security systems.\nDeep knowledge of: Operating systems, infrastructure, cloud platforms, and hybrid environments\nAutomation frameworks and pipeline‑driven enforcement models\nAbility to interpret and secure code written in multiple languages, with automation as the primary mitigation strategy.\nExperience integrating security tooling via APIs and pipelines, not manual review.\nFamiliarity with security intelligence ingestion and automation, including: CVE feeds\nSecurity advisories\nAutomated alerting and remediation workflows\nStrong understanding of cybersecurity, privacy, and AI governance requirements, with experience translating them into automated controls.\nAbility to concurrently deliver multiple security automation initiatives. Minimum Qualifications Bachelor's degree in Computer Science, Cybersecurity, IT Security, or equivalent experience.\nExperience in DevOps, SecOps, DevSecOps, or MLOps, with a strong automation focus.\nDemonstrated success implementing automated Secure SDLC pipelines.\nAbility to evaluate code and architecture risk and remediate through automation, not policy alone.\nFamiliarity with security frameworks and scoring systems:

MITRE ATT&CK

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Security & Agentic AI DevSecOps Engineer - Milpitas, CA