Systems Integration Specialist

NTT DATA North America; Hyderabad; On-site; INR 2,000,000 - 3,500,000; Full time

Job summary

NTT DATA North America in Hyderabad seeks a DevOps leader to architect production-grade AI/ML and GenAI solutions, embedding secure DevSecOps across multi-cloud environments. The role blends advanced AI expertise with cloud architecture, automation, and security leadership to drive enterprise modernization.

You will build scalable AI platforms, design data pipelines, deploy containerized services with Kubernetes and Docker, and lead governance and risk assessments with stakeholders across the

Qualifications

• 3+ years in enterprise architecture, cloud engineering, or platform leadership.
• 3+ years designing AI/ML or GenAI solutions in production.
• Strong Python and AI framework expertise.
• Deep knowledge of LLMs, RAG, and agentic architectures.
• Hands-on with Kubernetes, Docker, and CI/CD.
• Strong cloud architecture experience (AWS/Azure/GCP).
• Experience implementing DevSecOps practices.
• Knowledge of enterprise security frameworks and cloud security controls.
• Experience designing high-availability distributed systems.

Responsibilities

• Architect AI solutions across multi-cloud environments (AWS/Azure/GCP).
• Design scalable data pipelines and model serving infrastructure.
• Implement containerization (Docker) and orchestration (Kubernetes).
• Build high-availability, resilient AI platforms with performance optimization.
• Establish CI/CD pipelines for AI/ML workloads.
• Implement IaC (Terraform, ARM, CloudFormation).
• Build automated model deployment and monitoring pipelines (MLOps).
• Integrate AI into DevSecOps frameworks for secure delivery.
• Architect secure AI systems with Zero Trust principles.
• Collaborate with security teams for risk assessments and governance.

Skills

Python

AI frameworks

Kubernetes

Docker

CI/CD pipelines

Terraform

Cloud architecture

DevSecOps

Security frameworks

Tools

Kubernetes

Docker

Terraform

CloudFormation

ARM

Job description

Role Overview

We are seeking a highly accomplished DevOps candidate. This role requires technologist capable of architecting production-grade AI/ML and GenAI solutions while embedding secure DevSecOps practices across multi-cloud environments. The ideal candidate combines deep AI expertise with strong cloud architecture, automation, and security leadership.

Key Responsibilities

Cloud & Platform Engineering

• Architect AI solutions across AWS, Azure, or GCP environments.
• Design scalable data pipelines, model serving infrastructure, and distributed systems.
• Implement containerization (Docker) and orchestration (Kubernetes).
• Build high-availability, resilient AI platforms with performance optimization.

DevOps & MLOps Integration

• Establish CI/CD pipelines for AI/ML workloads.
• Implement Infrastructure as Code (Terraform, ARM, CloudFormation).
• Build automated model deployment and monitoring pipelines (MLOps).
• Integrate AI into DevSecOps frameworks for secure continuous delivery.

Security & Governance

• Architect secure AI systems adhering to Zero Trust principles.
• Implement model security controls (data protection, encryption, access control, secrets management).
• Conduct threat modeling for AI workloads (prompt injection, model poisoning, drift).
• Ensure compliance with enterprise security, regulatory, and audit requirements.
• Collaborate with security teams to perform red-teaming and AI risk assessments.

Stakeholder & Strategic Leadership

• Work closely with stakeholders to define AI transformation roadmaps.
• Provide architectural governance and technical mentorship to engineering teams.
• Evaluate emerging AI technologies and define adoption strategies.
• Drive innovation initiatives aligned with enterprise modernization goals.

Required Qualifications

• 3+ years of experience in enterprise architecture, cloud engineering, or platform leadership.
• 3+years designing and deploying AI/ML or GenAI solutions in production.
• Strong expertise in Python, AI frameworks (TensorFlow, PyTorch, LangChain, etc.).
• Deep understanding of LLM architecture, RAG systems, and agentic frameworks.
• Hands-on experience with Kubernetes, Docker, CI/CD pipelines.
• Strong cloud architecture experience (AWS/Azure/GCP certifications preferred).
• Experience implementing DevSecOps practices.
• Strong knowledge of enterprise security frameworks and cloud security controls.
• Experience designing high-availability distributed systems.

Preferred Qualifications

• Experience building enterprise AI platforms (AIOps, self-healing systems, automation).
• Knowledge of data governance and enterprise knowledge graphs.
• Experience integrating AI with ITSM platforms (ServiceNow, Remedy).
• Cloud or Security certifications (AWS/Azure Architect, CISSP, CCSP, etc.).
• Experience leading global, cross-functional technical teams.