AI Architect and Systems Integration Specialist

NTT DATA Global Delivery Services Ltd; Hyderabad; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

NTT DATA Global Delivery Services Ltd seeks an AI Architect to design and govern enterprise AI platforms integrated with DevOps, Cloud, and Security frameworks. The role requires producing production-grade AI/ML and GenAI solutions while embedding secure DevSecOps across multi-cloud environments.

The ideal candidate blends deep AI expertise with cloud architecture, automation, and security leadership, leading AI lifecycle management and governance across teams and platforms.

Qualifications

• Experience architecting enterprise AI/ML or GenAI platforms.
• Hands-on with Kubernetes, Docker, and CI/CD pipelines in production.
• Strong cloud experience across AWS/Azure/GCP.
• Knowledge of DevSecOps and cloud security controls.
• Ability to design high-availability distributed AI systems.

Responsibilities

• Lead design and governance of enterprise AI/ML and GenAI platforms.
• Define scalable AI reference architectures aligned with business goals.
• Manage end-to-end AI lifecycle: development, deployment, monitoring, governance.
• Establish AI explainability, observability, and ethical practices.
• Architect AI across multi-cloud (AWS/Azure/GCP) environments.
• Design data pipelines, model serving infra, and distributed systems.
• Implement containerization and orchestration (Docker, Kubernetes).
• Build high-availability AI platforms with performance optimization.
• Establish CI/CD pipelines for AI/ML workloads (MLOps).
• Implement IaC (Terraform, ARM, CloudFormation).
• Security integration into DevSecOps for secure delivery.
• Conduct AI risk assessments and threat modeling.
• Collaborate with security teams and stakeholders on AI transformation roadmaps.

Skills

Python

TensorFlow

PyTorch

LangChain

LLM architecture

RAG systems

Kubernetes

Docker

CI/CD pipelines

Cloud architecture

DevSecOps

Security controls

Threat modeling

Tools

Terraform

CloudFormation

ARM Templates

Jenkins

Job description

Systems Integration Specialist Role Overview

We are seeking a highly accomplished AI Architect to lead the design, implementation, and governance of enterprise-scale AI platforms integrated with DevOps, Cloud, and Security frameworks. This role requires a 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

• AI & Architecture Leadership Design and architect enterprise AI/ML and GenAI platforms (LLMs, RAG, agentic AI, AIOps, automation).
• Define scalable AI reference architectures aligned with business objectives.
• Lead end-to-end AI lifecycle management: model development, validation, deployment, monitoring, and governance.
• Establish standards for AI explainability, observability, and ethical AI practices.
• 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.

Leadership Competencies

• Strategic thinking and enterprise vision.
• Strong executive communication skills.
• Ability to translate complex AI concepts into business value.
• Governance-driven mindset with innovation orientation.

Experience Level Mid Level .