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

NTT DATA, Inc.; Atlanta (GA); Hybrid; USD 87,952 - 162,875; Full time

Job summary

NTT DATA seeks a Senior AI DevOps Engineer to design, build, and operate AI-powered CI/CD pipelines and MCP-enabled services. You will collaborate with Platform Engineering, DevOps, Security, SRE, and AI teams to deliver secure, scalable cloud-native solutions that accelerate software delivery while enhancing reliability and observability.

Responsibilities include deploying AI-driven workflows, implementing secure access controls, and advancing automation across AWS/Azure/GCP environments.

Qualifications

• 7+ years in DevOps, Platform/SRE, or cloud engineering.
• 4+ years designing and supporting enterprise CI/CD pipelines.
• 3+ years cloud engineering in AWS, Azure, or Google Cloud.
• Strong experience with Kubernetes and Docker in production.
• IaC experience with Terraform, OpenTofu, Pulumi, Terragrunt, or similar.
• Experience integrating enterprise LLM platforms into workflows.
• Experience with AI orchestration frameworks and MCP (Model Context Protocol).
• DevSecOps practices including SAST/DAST and secrets management.

Responsibilities

• Design, build, and optimize AI-enabled CI/CD pipelines.
• Develop MCP clients/servers connecting enterprise LLMs with tools and infra.
• Integrate LLM-powered workflows for code reviews, testing, security analysis, and release validation.
• Build and maintain enterprise CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins, CircleCI, ArgoCD).
• Implement AI-driven ChatOps for deployment pipelines and cloud environments.
• Design remediation workflows for incident detection and root-cause analysis.
• Deploy and manage containerized apps with Kubernetes and Docker across cloud providers.
• Build AI-powered observability using Datadog, Prometheus, Grafana, CloudWatch, etc.
• Implement security guardrails: RBAC, least-privilege, audit logging, approvals.
• Identify and implement intelligent automation opportunities with multiple teams.
• Create reusable automation frameworks, dashboards, and engineering best practices.

Skills

DevOps

Cloud

SRE

CI/CD

Kubernetes

Docker

Security

AI/ML Ops

GitOps

Observability

Education

Bachelor’s degree in CS/Engineering

Tools

Kubernetes

Docker

Terraform/OpenTofu

CloudFormation/Terragrunt

Open Policy Agent

Job description

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

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

Position Summary

We're looking for an experienced Senior AI DevOps Engineer to help build the next generation of AI-powered software delivery and cloud operations. In this role, you'll combine modern DevOps 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, DevOps, 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.
• 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.
• 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.
• 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.

What Makes You Successful

• Passion for automation and continuously improving engineering productivity.
• Security-first mindset with practical experience implementing safe, responsible AI automation.
• Ability to bridge DevOps, Platform Engineering, AI, Security, and Software Engineering disciplines.
• Strong problem-solving skills with an ownership mentality from design through production support.
• Comfortable leading technical initiatives and mentoring engineering teams on modern AI-enabled development practices.

Education

Bachelor's degree in Computer Science, Engineering, Information Technology, or a related discipline (or equivalent professional experience).

Work Location

Hybrid schedule with three days per week onsite as required by the client or project.

Pay Transparency

Where required by law, NTT DATA provides a reasonable range of compensation for specific roles. The starting pay range for this remote role is $87,952-$162,875. This range reflects the minimum and maximum target compensation for the position across all US locations. Actual compensation will depend on a number of factors, including the candidate’s actual work location, relevant experience, technical skills, and other qualifications.

This position is eligible for company benefits including medical, dental, and vision insurance with an employer contribution, flexible spending or health savings account, life and AD&D insurance, short- and long-term disability coverage, paid time off, employee assistance, participation in a 401k program with company match, and additional voluntary or legally-required benefits.

About NTT DATA

NTT DATA is a $30+ billion business and technology services leader, serving 75% of the Fortune Global 100. We are committed to accelerating client success and positively impacting society through responsible innovation. We are one of the world’s leading AI and digital infrastructure providers, with unmatched capabilities in enterprise-scale AI, cloud, security, connectivity, data centers and application services. Our consulting and industry solutions help organizations and society move confidently and sustainably into the digital future. As a Global Top Employer, we have experts in more than 50 countries. We also offer clients access to a robust ecosystem of innovation centers as well as established and start-up partners. NTT DATA is part of NTT Group, which invests over $3 billion each year in R&D.

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