Senior DevSecOps Platform Engineer, AI Automation

About the role

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.

Responsibilities

• 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.
• 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.
• 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.
• 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.

Qualifications

• 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.