Senior AI Ops​/DevOps Engineer

Senior AI Ops / Dev Ops Engineer

Position Overview:

Client needs immediate Senior AI Ops / Dev Ops Engineer

The ideal candidate is a senior hands-on Dev Ops engineer with strong cloud, automation, Kubernetes, and CI/CD expertise, combined with practical experience applying AI, LLM agents, and MCP-based integrations to modern engineering workflows. This role will help create a secure AI-driven delivery ecosystem that accelerates software engineering velocity while maintaining strong governance, reliability, auditability, and operational control. This role is crucial to show the efficiency.

Position General Duties and Tasks:

Day to Day Job Duties

The Senior AI Ops / Dev Ops Engineer will architect, build, and manage next-generation AI-driven CI/CD and cloud operations ecosystems. This role will go beyond traditional Dev Ops automation by integrating LLM agents, Model Context Protocol servers, intelligent observability, and secure AI-assisted workflows into the software delivery lifecycle.

• Architect, build, and manage AI-enabled CI/CD pipelines that improve developer productivity, code quality, release reliability, and deployment speed.
• Design and deploy production-grade Model Context Protocol clients and servers to securely connect enterprise LLMs with engineering tools, repositories, cloud infrastructure, and observability platforms.
• Develop custom MCP servers using Python, Type Script, Node.js, or JavaScript to expose logs, infrastructure metrics, deployment data, and internal tools to authorized AI agents.
• Integrate LLM agents into developer workflows to support automated code review, vulnerability detection, test generation, release validation, and infrastructure recommendations.
• Build and maintain robust CI/CD pipelines using Git Hub Actions, Git Lab CI, CircleCI, ArgoCD, Jenkins, or similar tools.
• Implement Chat Ops 2.0 capabilities that allow engineers to interact with deployment pipelines, cloud environments, logs, and operational workflows using secure conversational interfaces.
• Create safe autonomous remediation workflows for log analysis, incident triage, root-cause analysis, and infrastructure issue resolution.
• Build guardrails that allow AI agents to generate, inspect, and safely execute Infrastructure as Code using Terraform, Open Tofu, Terragrunt, Pulumi, Crossplane, or similar tools.
• Manage containerized workloads using Docker and Kubernetes platforms such as AWS EKS, Azure AKS, or Google GKE.
• Integrate AI-driven observability workflows with platforms such as Datadog, Prometheus, Grafana, Cloud Watch, Splunk, Dynatrace, or ELK.
• Implement AI safety controls including role-based access control, least-privilege execution, human-in-the-loop approvals, audit logging, rollback mechanisms, and secure tool access.
• Partner with software engineering, Dev Ops, SRE, security, platform, and data/AI teams to identify opportunities for intelligent automation.
• Create reusable automation frameworks, runbooks, dashboards, documentation, and enablement materials for engineering teams.
• Drive an “automate everything” culture by reducing manual toil and improving operational efficiency across cloud and software delivery processes.

Basic Qualifications:

• Minimum 7+ years of experience in Dev Ops, Cloud Engineering, SRE, Platform Engineering, or Infrastructure Automation.
• Minimum 4+ years of hands-on experience designing and managing CI/CD pipelines using Git Hub Actions, Git Lab CI, CircleCI, Jenkins, ArgoCD, or similar platforms.
• Minimum 3+ years of experience managing scalable cloud environments in AWS, Azure, or GCP, with strong preference for AWS.
• Strong hands-on experience with Kubernetes, Docker, and production container orchestration platforms such as EKS, AKS, or GKE.
• Advanced proficiency with Infrastructure as Code tools such as Terraform, Open Tofu, Terragrunt, Pulumi, Cloud Formation, or Crossplane.
• Strong programming and scripting experience using Python, Type Script, JavaScript, Bash, or Go.
• Practical experience working with LLM APIs such as OpenAI, Anthropic, or similar enterprise AI platforms.
• Experience with AI orchestration or agentic frameworks such as Lang Chain, CrewAI, Llama Index, or similar tools.
• Strong…