AI / GenAI Automation

• Design and implement AI-enabled DevSecOps and developer productivity solutions.
• Build and operationalize RAG pipelines and agent-based automation workflows.
• Develop intelligent remediation capabilities leveraging code, logs, telemetry, and security signals.
• Implement secure and governed LLM integration patterns using modern AI platforms and frameworks.
• Evaluate and optimize AI-enabled operational workflows for reliability, scalability, and cost efficiency.

Technical Leadership

• Drive technical direction across platform engineering initiatives.
• Operate independently across cross-functional programs and complex engineering environments.
• Mentor engineers and contribute to engineering standards and best practices.
• Collaborate across Security, Infrastructure, QA, SRE, and Software Engineering organizations.

Required Qualifications

Core Engineering & DevSecOps

• 8+ years of experience in Platform Engineering, DevSecOps, SRE, or related domains.
• Strong hands-on expertise building enterprise CI/CD pipelines using GitHub Actions, Jenkins, or similar tools.
• Strong software engineering background with proficiency in Python, Go, Java, or Node.js.
• Deep understanding of:
  • Cloud platforms (AWS, Azure, or GCP)
  • Kubernetes and container ecosystems
  • Infrastructure as Code
  • Distributed systems and microservices architectures
• Strong understanding of SDLC, testing, release engineering, and developer platform ecosystems.

Security

• Strong knowledge of Secure SDLC and DevSecOps principles.
• Experience implementing SAST, DAST, SCA, and policy-as-code frameworks.
• Experience with IAM, secrets management, governance, and compliance automation.
• Proven experience driving shift-left security initiatives.

AI / GenAI

• Practical experience leveraging LLMs in engineering or operational workflows.
• Experience building:
  • RAG pipelines
  • Agent-based workflows
  • AI-assisted automation capabilities
• Understanding of:
  • Embeddings and semantic search
  • LLM governance and security risks
  • Responsible AI implementation practices

Preferred Qualifications

• Experience with AIOps and observability platforms.
• Familiarity with MLOps pipelines and model lifecycle management.
• Experience with enterprise developer platforms and engineering enablement tooling.
• Knowledge of Zero Trust architecture and compliance automation frameworks.
• Exposure to AI governance and operational risk management practices.

Equinix is committed to ensuring that our employment process is open to all individuals, including those with a disability. If you are a qualified candidate and need assistance or an accommodation, please let us know by completing this form.

Equinix is an Equal Employment Opportunity and, in the U.S., an Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to unlawful consideration of race, color, religion, creed, national or ethnic origin, ancestry, place of birth, citizenship, sex, pregnancy / childbirth or related medical conditions, sexual orientation, gender identity or expression, marital or domestic partnership status, age, veteran or military status, physical or mental disability, medical condition, genetic information, political / organizational affiliation, status as a victim or family member of a victim of crime or abuse, or any other status protected by applicable law.

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This posting is a new position within our organization.