Senior AI DevOps Engineer; AI Ops​/Platform Engineering; Hybrid

Senior AI Dev Ops Engineer (AI Ops / Platform Engineering) (Hybrid)

NTT DATA Services strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now. We are currently seeking a Senior AI Dev Ops Engineer (AI Ops / Platform Engineering) to join our team in Atlanta, Georgia (US-GA), United States (US).

Senior AI Dev Ops Engineer (AI Ops / Platform Engineering) Position Summary

We're looking for an experienced Senior AI Dev Ops Engineer to help build the next generation of AI-powered software delivery and cloud operations. In this role, you'll combine modern Dev Ops practices with Generative AI, LLM agents, Model Context Protocol (MCP), and intelligent automation to transform how engineering teams build, deploy, and operate software. You'll partner with Platform Engineering, Dev Ops, Security, SRE, and AI teams to design secure, scalable, cloud-native solutions that accelerate software delivery while improving reliability, observability, and operational efficiency.

This is an opportunity to work on cutting-edge AI technologies that are redefining modern software engineering.

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, Type Script, 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 Git Hub Actions, Git Lab CI, Jenkins, CircleCI, ArgoCD, or similar platforms.
• Implement AI-driven Chat Ops 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, Open Tofu, Pulumi, Terragrunt, Cloud Formation, 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, Cloud Watch, 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 Dev Ops, Platform Engineering, Site Reliability Engineering (SRE), Cloud Engineering, or Infrastructure Automation.
• 4+ years designing and supporting enterprise CI/CD pipelines using Git Hub Actions, Git Lab 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, Open Tofu, Pulumi, Terragrunt, Cloud Formation, or similar tools.
• Strong programming skills in Python, Type Script, 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 Lang Chain, CrewAI, Llama Index, or similar technologies.
• Experience designing or implementing Model Context Protocol (MCP) clients and servers.
• Experience implementing Dev…