AI Ops / DevOps Engineer

NTT Data Americas, Inc.; Atlanta (GA); Hybrid; USD 82,656 - 96,432; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

401k with company match

Paid time off

Job summary

NTT DATA is seeking a Senior AI Ops / DevOps Engineer in Atlanta, GA. You will architect and manage AI-driven CI/CD and cloud operations, integrating LLM agents and Model Context Protocol servers with engineering tools, repositories, and observability platforms.

Responsibilities include building AI-enabled CI/CD pipelines, secure MCP client/server implementations, and AI-assisted workflows to improve deployment speed and reliability.

Qualifications

• 7+ years in DevOps/Cloud/SRE roles or similar.
• Experience designing and managing CI/CD pipelines across GitHub Actions, GitLab CI, CircleCI, Jenkins, ArgoCD or similar.

Responsibilities

• Architect AI-enabled CI/CD and cloud operations ecosystems.
• Design MCP clients/servers to connect enterprise LLMs with tools and infra.
• Develop AI‑driven automation inside CI/CD pipelines and Obs platforms.
• Integrate AI agents into workflows for code review, security, test generation, and deployments.
• Build and maintain robust CI/CD pipelines using major tools.

Skills

DevOps engineering

Cloud platforms

Kubernetes

Python/TypeScript/JavaScript

LLM APIs

CI/CD security

Observability

Terraform/OpenTofu/Crossplane

SRE/Platform engineering

Education

Bachelor's degree in CS/Engineering

Tools

GitHub Actions

GitLab CI

CircleCI

ArgoCD

Jenkins

Terraform

OpenTofu

Pulumi

CloudFormation

Docker

Kubernetes tools (EKS/AKS/GKE)

Job description

Req ID: 382452

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

Job Description – Senior AI Ops / DevOps Engineer

Day to Day Job Duties

The Senior AI Ops / DevOps Engineer will architect, build, and manage next-generation AI-driven CI/CD and cloud operations ecosystems. This role will go beyond traditional DevOps 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, TypeScript, 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 GitHub Actions, GitLab CI, CircleCI, ArgoCD, Jenkins, or similar tools.
• Implement ChatOps 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, OpenTofu, 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, CloudWatch, 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, DevOps, 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 DevOps, Cloud Engineering, SRE, Platform Engineering, or Infrastructure Automation.
• Minimum 4+ years of hands‑on experience designing and managing CI/CD pipelines using GitHub Actions, GitLab 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, OpenTofu, Terragrunt, Pulumi, CloudFormation, or Crossplane.
• Strong programming and scripting experience using Python, TypeScript, 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 LangChain, CrewAI, LlamaIndex, or similar tools.
• Strong understanding of the Model Context Protocol ecosystem and experience designing or integrating MCP clients and servers.
• Experience integrating DevSecOps 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 HashiCorp Vault, AWS Secrets Manager, Azure Key Vault, or similar platforms.
• Experience with observability, monitoring, logging, and alerting platforms such as Datadog, Prometheus, Grafana, CloudWatch, Splunk, Dynatrace, or ELK.
• Familiarity with security and compliance frameworks such as SOC2, ISO27001, or enterprise audit control environments.
• Ability to troubleshoot complex pipeline, infrastructure, deployment, and production issues across cloud‑native environments.

Preferred / Nice to Have

• Experience building AI‑assisted infrastructure provisioning workflows.
• Experience implementing autonomous or semi‑autonomous incident response and remediation capabilities.
• Experience with MLOps, model deployment pipelines, model monitoring, MLflow, SageMaker, or equivalent platforms.
• Experience implementing human‑in‑the‑loop approval models for AI‑generated operational actions.
• Experience with policy‑as‑code tools such as Open Policy Agent, Sentinel, Checkov, or similar solutions.
• Experience working in regulated industries such as banking, financial services, healthcare, or insurance.
• Experience with GitOps operating models using ArgoCD, Flux, or similar tools.
• AWS, Kubernetes, DevOps, Security, or AI/ML certifications are a plus.

Soft Skills & Mindset

• Strong \"automate everything” mindset with a passion for reducing repetitive manual tasks and operational toil.
• Security‑first approach with practical skepticism of autonomous AI actions and a focus on validation, boundaries, approvals, and rollback.
• Ability to bridge traditional software engineering, DevOps, SRE, security, and data/AI teams.
• Strong communication skills with the ability to explain complex AI‑enabled DevOps concepts to both technical and leadership audiences.
• Collaborative educator who can help upskill engineering teams on AI‑assisted delivery, secure automation, and modern DevOps practices.
• Ownership mindset with the ability to design solutions, implement them hands‑on, and support them in production.

Travel

This position requires 3 days in office per the client/project requirement.

Degree

Bachelor's degree in Computer Science, Engineering, Information Technology, or equivalent work experience.

Where required by law, NTT DATA provides a reasonable range of compensation for specific roles. The starting hourly range for this remote role is ($60-$70/hour). This range reflects the minimum and maximum target compensation for the position across all US locations. Actual compensation will depend on several factors, including the candidate's actual work location, relevant experience, technical skills, and other qualifications. This position may also be eligible for incentive compensation based on individual and/or company performance.

Company benefits may include medical, dental, and vision insurance, 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 trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate, optimize and transform for long term success. As a Global Top Employer, we have diverse experts in more than 50 countries and a robust partner ecosystem of established and start‑up companies. Our services include business and technology consulting, data and artificial intelligence, industry solutions, as well as the development, implementation and management of applications, infrastructure and connectivity. We are one of the leading providers of digital and AI infrastructure in the world. NTT DATA is a part of NTT Group, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Visit us at us.nttdata.com

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