Description

What You'll Do:

• Design, build, and optimize AI-enabled CI/CD pipelines that improve developer productivity, deployment speed, and software quality.
• Develop and deploy Model Context Protocol (MCP) clients and servers that securely connect enterprise LLMs with engineering tools, cloud infrastructure, and operational platforms.
• Build custom MCP services using Python, TypeScript, JavaScript, or Node.js to expose infrastructure, deployment, monitoring, and operational data to authorized AI agents.
• Integrate LLM-powered workflows for automated code reviews, testing, security analysis, release validation, and infrastructure recommendations.
• Build and maintain enterprise CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, CircleCI, ArgoCD, or similar platforms.
• Implement AI-driven ChatOps capabilities that enable engineers to interact with deployment pipelines, cloud environments, and operational tools through secure conversational interfaces.
• Design intelligent remediation workflows for incident detection, root cause analysis, log analysis, and operational troubleshooting.
• Develop secure Infrastructure-as-Code automation using Terraform, OpenTofu, Pulumi, Terragrunt, CloudFormation, or similar technologies.
• Deploy and manage containerized applications using Kubernetes and Docker across AWS, Azure, or Google Cloud.
• Build AI-powered observability solutions leveraging Datadog, Prometheus, Grafana, CloudWatch, Splunk, Dynatrace, ELK, or similar platforms.
• Implement security guardrails including RBAC, least-privilege access, approval workflows, audit logging, rollback mechanisms, and secure AI tool access.
• Partner with Engineering, Platform, Security, SRE, and AI teams to identify and implement intelligent automation opportunities.
• Create reusable automation frameworks, documentation, dashboards, and engineering best practices that scale across the organization.

Required Qualifications

• 7+ years of experience in DevOps, Platform Engineering, Site Reliability Engineering (SRE), Cloud Engineering, or Infrastructure Automation.
• 4+ years designing and supporting enterprise CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, CircleCI, ArgoCD, or similar tools.
• 3+ years of cloud engineering experience in AWS, Azure, or Google Cloud (AWS preferred).
• Strong experience deploying and managing Kubernetes and Docker in production environments (EKS, AKS, or GKE).
• Hands-on experience with Infrastructure as Code using Terraform, OpenTofu, Pulumi, Terragrunt, CloudFormation, or similar tools.
• Strong programming skills in Python, TypeScript, JavaScript, Bash, Go, or similar languages.
• Experience integrating enterprise LLM platforms such as OpenAI, Anthropic, or equivalent AI services into engineering workflows.
• Experience with AI orchestration frameworks such as LangChain, CrewAI, LlamaIndex, or similar technologies.
• Experience designing or implementing Model Context Protocol (MCP) clients and servers.
• Experience implementing DevSecOps practices including SAST, DAST, dependency scanning, container security, secrets management, and vulnerability management.
• Experience with secrets management solutions such as HashiCorp Vault, AWS Secrets Manager, or Azure Key Vault.
• Strong experience with monitoring, logging, and observability platforms such as Datadog, Grafana, Prometheus, CloudWatch, Splunk, Dynatrace, or ELK.
• Excellent troubleshooting skills across cloud infrastructure, CI/CD pipelines, Kubernetes, and production systems.
• Strong communication skills and the ability to collaborate across engineering, security, and AI teams.

Preferred Qualifications

• Experience building AI-assisted infrastructure provisioning and deployment workflows.
• Experience implementing autonomous or AI-assisted incident response and operational remediation.
• Experience with MLOps platforms including MLflow, Amazon SageMaker, Vertex AI, Azure ML, or similar technologies.
• Experience implementing human-in-the-loop approval workflows for AI-generated operational actions.
• Knowledge of Policy-as-Code frameworks such as Open Policy Agent (OPA), Sentinel, or Checkov.
• Experience with GitOps platforms such as ArgoCD or Flux.
• Experience working within regulated industries such as financial services, healthcare, insurance, or government.
• AWS, Kubernetes, DevOps, Security, or AI/ML certifications

Key Skills

Education

Any Graduate