Dxc Technology
AIDevOpsEngineer(MLOps&Cloud)
Neural analysis suggests this role is
optimal for Senior candidates.
“AI DevOps Engineer (MLOps & Cloud) at Dxc Technology. Skills: AI DevOps, MLOps, Cloud Platforms (AWS, Azure, GCP), Infrastructure as Code (Terraform), Containerization and Orchestration (Docker, Kubernetes), CI/CD, Scripting and Automation (Python, Bash), DevSecOps. Design, implement, and maintain scalable, secure cloud infrastructure for AI/ML solutions. Build and manage Infrastructure as Code (IaC)”
What You'll Achieve.
ensure high system reliability and availability; focus on automation, scalability, and production-ready AI systems
Industry & Context.
problem-solving and analytical thinking; Troubleshoot production issues
What They're Looking For.
Must Have
5+ years of experience in DevOps, SRE, or platform engineering, experience in MLOps and deployment of AI/ML solutions in production, Proficiency with cloud platforms (AWS, Azure, or GCP) and related AI services, Expertise in Infrastructure as Code (Terraform, CloudFormation, ARM templates), Hands-on experience with containerisation and orchestration (Docker, Kubernetes, Helm), CI/CD experience (GitHub Actions, GitLab CI, Jenkins, Azure DevOps), Proficiency in scripting and automation (Python, Bash), Experience with monitoring and observability tools (Prometheus, Grafana, ELK, Datadog), Knowledge of DevSecOps practices and security standards, Experience with secrets and configuration management (Vault, AWS Secrets Manager)
Nice to Have
Experience optimising AI workloads using GPUs, Ability to diagnose and resolve issues using AI-assisted tools, problem-solving and analytical thinking, Pragmatic approach balancing automation, speed, and reliability, Attention to detail in infrastructure design and security, Proactive, with ownership and initiative, collaboration and support mindset, Comfortable working in fast-paced, agile environments
What You'll Do.
and maintain scalable
secure cloud infrastructure for AI/ML solutions
Build and manage Infrastructure as Code (IaC)
Develop and maintain CI/CD pipelines for AI applications and model deployment
Support end-to-end MLOps lifecycle (training
Automate deployments using best practices (blue/green
and observability (logs
tracing) for production systems
Use AI tools (e. g. Copilot
Cursor) to accelerate scripting
and incident resolution
Troubleshoot production issues and ensure high system reliability and availability
Support developers and data scientists on DevOps tooling and best practices
Implement DevSecOps standards
Maintain clear technical documentation for infrastructure and processes
How You'll Work.
Team & Collaboration
Support developers and data scientists on DevOps tooling and best practices; Close collaboration with AI engineers, data scientists, and infrastructure teams
Communication Scope
English-speaking environment (fluency required)
Full Job Description
**Job Description:** DXC Technology (NYSE: DXC) is a leading enterprise technology and innovation partner delivering software, services, and solutions to global enterprises and public sector organizations — helping them harness AI to drive outcomes at a time of exponential change with speed. With deep expertise in Managed Infrastructure Services, Application Modernization, and Industry-Specific Software Solutions, DXC modernizes, secures, and operates some of the world's most complex technology estates. Learn more on [ _dxc.com_](https://nam12.safelinks.protection.outlook.com/?url=https://demo.dxc.com/content/dxc&data=05%7c02%7calbena.dimitrova%40dxc.com%7c853ee652022e4cdde23808de373e4283%7c93f33571550f43cfb09fcd331338d086%7c0%7c0%7c639008937734407635%7cUnknown%7cTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7c0%7c%7c%7c&sdata=teALgMQnki5TpuzmW1wyAbzUJ%2BNCj8zYWTpcYcoU8ho%3D&reserved=0). **Key Responsibilities** * Design, implement, and maintain scalable, secure cloud infrastructure for AI/ML solutions * Build and manage Infrastructure as Code (IaC) using tools such as Terraform or CloudFormation * Develop and maintain CI/CD pipelines for AI applications and model deployment * Support end-to-end MLOps lifecycle (training, versioning, deployment, monitoring) * Automate deployments using best practices (blue/green, canary releases, rollback strategies) * Configure monitoring, alerting, and observability (logs, metrics, tracing) for production systems * Optimize performance, scalability, and cost (compute, storage, GPU usage) * Use AI tools (e.g. Copilot, ChatGPT, Claude, Cursor) to accelerate scripting, automation, and incident resolution * Troubleshoot production issues and ensure high system reliability and availability * Support developers and data scientists on DevOps tooling and best practices * Implement DevSecOps standards, including security, secrets management, and compliance * Maintain clear technica
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