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

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

Senior AI DevOps Engineer (AI Ops / Platform Engineering) 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.
• Build custom MCP services using Python, TypeScript, 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 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.
• Develop secure Infrastructure-as-Code automation using Terraform, OpenTofu, Pulumi, Terragrunt, CloudFormation, 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, 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.
• Strong programming skills in Python, TypeScript, 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 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. Whenever possible, we hire locally to NTT DATA offices or client sites. This ensures we can provide timely and effective support tailored to each client's needs. While many positions offer remote or hybrid work options, these arrangements are subject to change based on client requirements. For employees near an NTT DATA office or client site, in-office attendance may be required for meetings or events, depending on business needs. At NTT DATA, we are committed to staying flexible and meeting the evolving needs of both our clients and employees.

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