Senior MLOps / AIOps Platform Engineer

Req ID:    

We are currently seeking a Senior MLOps / AIOps Platform Engineer to join our team in Chennai, Tamil Nādu (IN-TN), India (IN).

Job Summary 
We are seeking a Senior MLOps / AIOps Platform Engineer with deep DevSecOps expertise and hands-on experience managing enterprise-grade AI/ML platforms. This critical role focuses on building, configuring, and operationalizing secure, scalable, and reusable infrastructure and pipelines that support AI and ML initiatives across the enterprise. The ideal candidate will have a strong background in Infrastructure as Code (IaC), pipeline automation, and platform engineering, with specific experience configuring and maintaining IBM watsonx and Google Cloud Vertex AI environments.

Key Responsibilities
Platform Engineering & Operations
• Lead the provisioning, configuration, and ongoing support of IBM watsonx and Google Cloud Vertex AI platforms.
• Ensure platforms are production-ready, secure, cost-efficient, and performant across training, inference, and orchestration workflows.
• Manage lifecycle tasks such as patching, upgrades, integrations, and service reliability.
• Partner with security, compliance, and product teams to align platforms with enterprise and regulatory standards.
Enterprise MLOps / AIOps Enablement
• Define and implement standardized MLOps/AIOps practices across business units for consistency and scalability.
• Build and maintain reusable workflows for model development, deployment, retraining, and monitoring.
• Provide onboarding, enablement, and support to AI/ML teams adopting enterprise platforms and tools.
• Support development/deployment of GenAI applications and maintain them at an Enterprise scale.
DevSecOps Integration
• Embed security and compliance guardrails across the ML lifecycle, including CI/CD pipelines and IaC templates.
• Implement policy-as-code, access controls, vulnerability scanning, and automated compliance checks.
• Ensure all deployments meet enterprise and regulatory requirements (HIPAA, SOX, FedRAMP, etc.).
Infrastructure as Code & Automation
• Design and maintain IaC templates (Terraform, Pulumi, Ansible, CloudFormation) for reproducible ML infrastructure.
• Build and optimize CI/CD pipelines for AI/ML assets including data pipelines, training workflows, deployment artifacts, and monitoring systems.
• Enforce best practices around automation, reusability, and observability of infrastructure and workflows.
Monitoring, Logging & Observability
• Implement comprehensive observability for AI/ML workloads using Prometheus, Grafana, Stackdriver, or Datadog.
• Monitor both infrastructure health (CPU, memory, cost) and ML-specific metrics (model drift, data integrity, anomaly detection).
• Define KPIs and usage metrics to measure platform performance, adoption, and operational health.

Qualifications
Education
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.
Experience
• 5+ years in MLOps, DevOps, Platform Engineering, or Infrastructure Engineering.
• 2+ years applying DevSecOps practices (secure CI/CD, vulnerability management, policy enforcement).
• Hands-on experience configuring and managing enterprise AI/ML platforms (IBM watsonx, Google Vertex AI).
• Demonstrated success in building and scaling ML infrastructure, automation pipelines, and platform support models.
Technical Skills
• Proficiency with IaC tools (Terraform, Pulumi, Ansible, CloudFormation).
• Strong scripting skills in Python and Bash.
• Deep understanding of containerization and orchestration (Docker, Kubernetes).
• Experience with model lifecycle tools (MLflow, TFX, Vertex Pipelines, or equivalents).
• Familiarity with secrets management, policy-as-code, access control, and monitoring tools.
• Working knowledge of data engineering concepts and their integration into ML pipelines.
Preferred
• Cloud certifications (e.g., GCP Professional ML Engineer, AWS DevOps Engineer, IBM Cloud AI Engineer).
• Experience supporting platforms in regulated industries (HIPAA, FedRAMP, SOX, PCI-DSS).
• Contributions to open-source projects in MLOps, automation, or DevSecOps.
• Familiarity with responsible AI practices including governance, fairness, interpretability, and explainability.
• Hands-on experience with enterprise feature stores, model monitoring frameworks, and fairness toolkits.

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