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AI Ops​/DevOps Engineer

Job in Atlanta, Fulton County, Georgia, 30383, USA
Listing for: NTT Data Americas, Inc.
Full Time position
Listed on 2026-07-25
Job specializations:
  • Software Development
    AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 82656 - 96432 USD Yearly USD 82656.00 96432.00 YEAR
Job Description & How to Apply Below
Position: AI Ops / DevOps Engineer

Req

NTT DATA's Client is seeking a Senior AI Ops / Dev Ops Engineer to join their team in Atlanta, Georgia (US-GA), United States (US).

Job Description – Senior AI Ops / Dev Ops Engineer 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 understanding of the Model Context Protocol ecosystem and experience designing or integrating MCP clients and servers.
  • Experience integrating Dev Sec Ops  controls into CI/CD pipelines, including SAST, DAST, dependency scanning, container scanning, secrets scanning, and vulnerability management.
  • Strong knowledge of secret management and security tooling such as Hashi Corp Vault, AWS Secrets Manager, Azure Key Vault, or similar platforms.
  • Expe…
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