Senior DevSecOps Platform Engineer, AI Automation

About this role

Who are we? Equinix is the world’s digital infrastructure company®, shortening the path to connectivity to enable the innovations that enrich our work, life and planet.  

A place where tech thinkers and future builders turn bold ideas into breakthrough experiences, we welcome your unique perspective.

Help us challenge assumptions, uncover bias, and remove barriers—because progress starts with fresh ideas. You’ll find belonging, purpose, and a team that welcomes you—because when you feel valued, you’re empowered to do your best work.

Role Summary We are seeking a Senior DevSecOps / Platform Engineer to design, build, and operate secure CI/CD and platform automation capabilities enhanced with LLM-driven workflows. This hands-on role will embed security and compliance controls into the software delivery lifecycle, implement policy-as-code guardrails, and build AI-powered agents to reduce operational toil, accelerate remediation, and improve enterprise security posture. You’ll collaborate closely with Security, SRE/Infra Platform, and engineering teams to enable faster, safer software delivery while balancing speed, security, and cost. Key Responsibilities CI/CD & Platform Engineering • Build, maintain, and continuously improve secure CI/CD pipelines (e.g., GitHub Actions) and reusable workflow templates. • Develop platform automation that improves developer experience, reliability, and deployment consistency. • Engineer and maintain Infrastructure as Code (Terraform, Bicep, and/or CloudFormation) for repeatable environments. • Support cloud-native applications using containers and Kubernetes, including troubleshooting deployments and runtime issues.

Shift-Left Security & Compliance Automation • Integrate SAST, DAST, and SCA scanning tools into CI/CD with actionable reporting and automated gating. • Implement best practices for IAM and secrets management, minimizing credential exposure and enforcing least privilege. • Build and maintain policy-as-code controls that align to governance requirements and reduce manual compliance effort. • Partner with Security and engineering teams to align guardrails with practical delivery workflows.

AI / GenAI-Powered DevSecOps Automation • Implement LLM-enabled capabilities in pipelines and platforms using production-grade LLM services (e.g., GPT, Azure OpenAI, Claude, Llama). • Build and operationalize RAG pipelines for retrieving runbooks, standards, and historical incident/pipeline context. • Develop agent-based workflows (LangChain, LangGraph, CrewAI, AutoGen) to assist with diagnostics and remediation. • Develop agents that leverage code, logs, pipeline signals, and security findings to diagnose CI/CD failures, recommend fixes, and automate safe recovery actions within defined guardrails. • Apply LLM risk controls and mitigations (e.g., prompt injection, data leakage) including access boundaries and auditability.

Observability & Operational Excellence • Enhance platform observability and incident response by integrating AI-driven insights and automation. • Continuously tune and evaluate AI solutions for accuracy, safety, reliability, and cost. • Document standards, patterns, and runbooks; contribute to scalable onboarding and adoption.

How You’ll Spend Your Time (Typical Breakdown) • 30% – Building/enhancing CI/CD pipelines and platform automation • 25% – Implementing AI/LLM capabilities (agents, RAG, workflow automation) • 20% – Security engineering (scanning tools, policies, compliance) • 15% – Cloud infrastructure & Kubernetes support • 10% – Collaboration (architecture reviews, design discussions, support)

Required Qualifications (Must Have) Core Engineering & DevSecOps • 8+ years experience in DevSecOps / Platform Engineering or related roles. • Hands-on expertise with CI/CD pipeline engineering (e.g., GitHub Actions). • Strong programming skills in Python, Go, or Java. • Deep understanding of cloud platforms (AWS, Azure, or GCP). • Strong knowledge of microservices and distributed systems. • Strong knowledge of Infrastructure as Code (Terraform, Bicep, CloudFormation). • Strong knowledge of containers and Kubernetes.

Security • Strong knowledge of Secure SDLC / DevSecOps practices. • Experience integrating SAST, DAST, and SCA tools into delivery pipelines. • Solid experience with secrets management and IAM concepts and implementation. • Proven ability to implement shift-left security, guardrails, and policy-as-code.

AI / GenAI • Practical experience running LLMs in production (e.g., GPT, Azure OpenAI, Claude, Llama). • Experience building RAG pipelines. • Experience building agent-based workflows (e.g., LangChain, LangGraph, CrewAI, AutoGen). • Understanding of embeddings, semantic search, and NLP fundamentals. • Understanding of LLM risks (prompt injection, data leakage) and safe implementation patterns.

Preferred Qualifications (Nice to Have) • Experience with AIOps and/or observability platforms. • Familiarity with MLOps pipelines and model lifecycle management. • Experience with synthetic data generation/anonymization. • Experience with QA automation frameworks. • Knowledge of Zero Trust architecture. • Exposure to AI governance frameworks and compliance automation.

Success Measures (What Great Looks Like) • Measurable reduction in manual security/ops effort through automation and agentic workflows. • Improved application and infrastructure security posture via consistent scanning, policy controls, and guardrails. • Faster and more reliable delivery cycles (reduced pipeline failures, shorter time-to-remediate). • Increased adoption of secure, standardized CI/CD patterns across engineering teams. • AI capabilities operate safely with governance controls, auditability, and cost-aware design.

Realistic Job Preview (Important to Know) • This is a hands-on engineering role, not primarily strategy. • You will work in ambiguous, fast-evolving AI environments—expect iteration and experimentation. • A significant portion of effort involve

Similar jobs

• DevSecOps Platform Engineer, AI Automation — Equinix · Dallas Infomart Office DAI
• Senior Security Engineer, AI & DevSecOps — Atlasxhm · Canada; United States of America
• Senior Security Engineer - AI Security & Platforms — Ridgeline · Reno, NV; San Ramon, CA
• Senior Platform Engineer, AI — Trueanomalyinc · Denver, CO or Long Beach, CA
• Senior Platform Engineer, AI Systems — Strike · Remote
• Senior AI Platform Engineer — Alpaca · Remote
• Senior AI Platform Engineer — Expel · Remote
• Senior AI Platform Engineer — Afresh · San Francisco, CA