Security & Agentic AI DevSecOps Engineer

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
Policy‑driven prompt/instruction validation and misuse detection
Automated enforcement of agent‑to‑agent authentication and authorization
Implement continuous, automated threat modeling for: 
LLM pipelines
Agent orchestration frameworks
AI gateways and inference services
Build secure‑by‑default reference architectures where AI guardrails are enforced via: 
Configuration‑as‑code
Runtime policy engines
Automated security testing pipelines
Create 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
AI‑specific security testing (prompt injection, model misuse, data leakage)
Automated build and release policy enforcement (fail gates, conditional approvals)
Ensure all security checks are: 
Triggered automatically via CI/CD and MLOps pipelines
Enforced consistently across dev, test, and production
Automate security validation during: 
Design reviews (template‑driven controls)
Architecture reviews (reusable security patterns)
Pre‑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
Automated AI‑BOMs covering models, datasets, checkpoints, and training artifacts
Implement automated vulnerability, license, and provenance analysis: 
Continuous ingestion of CVEs and advisories
Automated policy enforcement for non‑compliant components
Integrate SBOM and AI‑BOM outputs into: 
CI/CD pipelines
Deployment gates
Audit and compliance reporting workflows
Runtime Security, Risk & Metrics Automation

Implement continuous, automated security monitoringacross: 
Application runtimes
AI/ML inference services
Agent workflows and interactions
Develop automated security metrics and telemetry to measure: 
Vulnerability exposure and remediation velocity
Secure SDLC and DevSecOps maturity
Model and AI risk posture over time
Automate security feedback loops so findings: 
Generate actionable tasks
Feed directly into engineering backlogs
Drive 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
Act as a  technical authority on AI security automation and DevSecOps.
Define reusable security automation patterns, templates, and reference implementations.
Partner with engineering, AI/ML, platform, and compliance teams to replace manual security workflows with automated controls.
Contribute to internal security standards that mandate automation by default.
 

Strong hands‑on experience designing automated Product Security or AI Security systems.
Deep knowledge of: 
Operating systems, infrastructure, cloud platforms, and hybrid environments
Automation frameworks and pipeline‑driven enforcement models
Ability to interpret and secure code written in multiple languages, with automation as the primary mitigation strategy.
Experience integrating security tooling via APIs and pipelines, not manual review.
Familiarity with security intelligence ingestion and automation, including: 
CVE feeds
Security advisories
Automated alerting and remediation workflows
Strong understanding of cybersecurity, privacy, and AI governance requirements, with experience translating them into automated controls.
Ability to concurrently deliver multiple security automation initiatives.
Minimum Qualifications

Bachelor’s degree in Computer Science, Cybersecurity, IT Security, or equivalent experience.
Experience in DevOps, SecOps, DevSecOps, or MLOps, with a strong automation focus.
Demonstrated success implementing automated Secure SDLC pipelines.
Ability to evaluate code and architecture risk and remediate through automation, not policy alone.
Familiarity with security frameworks and scoring systems: 
MITRE ATT&CK
CVSS
CWE
Strong technical communication skills and cross‑functional influence.