Senior AI Ops / DevOps Engineer

NTT DATA North America; Atlanta (GA); Hybride; USD 76 000 - 96 000; Plein temps

Résumé du poste

NTT DATA is seeking a Senior AI Ops / DevOps Engineer to architect and manage AI-driven CI/CD and cloud operations. You will integrate LLM agents, Model Context Protocol nodes, and intelligent observability into the software delivery lifecycle, building scalable, secure automation across AWS, Azure, and GCP.

You will implement guardrails for IaC execution, work with Terraform/OpenTofu/Pulumi, and partner with security, SRE, and data teams to accelerate velocity with governance.

Qualifications

• 7+ years in DevOps, Cloud/SRE, or related fields.
• 4+ years designing/managing CI/CD pipelines.
• 3+ years managing scalable cloud environments (AWS/Azure/GCP).
• Hands-on with Kubernetes, Docker, EKS/AKS/GKE.
• IaC experience with Terraform/OpenTofu/Terragrunt/Pulumi/Crossplane.

Responsabilités

• Architect and manage AI-driven CI/CD and cloud ops ecosystems.
• Design MCP clients/servers connecting enterprise LLMs to tools and infra.
• Develop MCP servers with Python/TypeScript/Node.js/JS to expose data to AI agents.
• Integrate LLM agents for code review, vulnerability detection, test generation.
• Build CI/CD pipelines with GitHub Actions, GitLab CI, CircleCI, Jenkins, ArgoCD.

Connaissances

CI/CD

Kubernetes

Docker

Python

TypeScript

JavaScript

Go

Shell

LLM APIs

LangChain

MCP

Observability

Security

Formation

Bachelor's degree in Computer Science, Engineering, IT, or equivalent

Outils

GitHub Actions

GitLab CI

CircleCI

ArgoCD

Jenkins

Terraform

OpenTofu

Pulumi

Terraform

CloudFormation

Description du poste

Company Overview:

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

Summary

The ideal candidate is a senior hands-on DevOps engineer with strong cloud, automation, Kubernetes, and CI/CD expertise, combined with practical experience applying AI, LLM agents, and MCP-based integrations to modern engineering workflows. This role will help create a secure AI-driven delivery ecosystem that accelerates software engineering velocity while maintaining strong governance, reliability, auditability, and operational control.

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

The starting hourly range for this remote role is ($55.00-$70.00/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.

NTT DATA endeavors to make https://us.nttdata.com accessible to any and all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please contact us at https://us.nttdata.com/en/contact-us. This contact information is for accommodation requests only and cannot be used to inquire about the status of applications.

NTT DATA is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. For our EEO Policy Statement, please click here. If you'd like more information on your EEO rights under the law, please click here. For Pay Transparency information, please click here.