Senior AI Ops​/DevOps Engineer; FTE​/Hybrid

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Date: Sep 27, 2026

Location: Atlanta, GA, US

Company: NTT DATA Services

NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us.

We are currently seeking a Senior AI Ops / Dev Ops Engineer (FTE / Hybrid) to join our team in Atlanta
, Georgia (US-GA),
United States (US).

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.
• 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, and 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.

• 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.
• 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 understanding of the Model Context Protocol ecosystem and experience designing or integrating MCP clients and…