Systems Integration Specialist Advisor

NTT DATA BUSINESS SOLUTIONS; Dadri; On-site; INR 1,800,000 - 4,000,000; Full time

Job summary

NTT DATA BUSINESS SOLUTIONS in Noida, Uttar Pradesh, India, seeks a Senior AI Architect to lead enterprise AI platform design, governance, and secure DevSecOps integration across multi-cloud environments.

You will architect production-grade AI/ML and GenAI solutions, oversee end-to-end AI lifecycle, establish standards for explainability and observability, and mentor teams. This role demands strong cloud, automation, and security leadership for scalable AI systems.

Qualifications

• 7–12+ years in enterprise architecture or platform leadership.
• 5+ years designing and deploying AI/ML or GenAI in production.
• Strong Python and AI frameworks experience.
• Deep knowledge of LLMs, RAG, and agentic AI concepts.
• Hands-on Kubernetes, Docker, and CI/CD in multi-cloud.
• Experience with DevSecOps and security controls.
• Knowledge of data governance and cloud security.

Responsibilities

• Design and govern enterprise AI platforms including AI/ML and GenAI capabilities.
• Define scalable AI reference architectures aligned with business goals.
• Lead end-to-end AI lifecycle management: development, validation, deployment, monitoring.
• Establish standards for explainability, observability, and ethical AI.
• Architect AI solutions across AWS/Azure/GCP and ensure high availability.
• Implement CI/CD pipelines and IaC for AI workloads; integrate DevSecOps.
• Collaborate with security teams on risk assessments and threat modeling.

Skills

Python

TensorFlow

PyTorch

LangChain

LLM Architectures

Kubernetes

Docker

CI/CD

DevSecOps

Cloud Architecture

Tools

Kubernetes

Docker

CI/CD

Terraform

AWS

Azure

GCP

Job description

We are currently seeking a Systems Integration Specialist Advisor to join our team in Noida, Uttar Pradesh, India.

Role Overview

We are seeking a highly accomplished Senior 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 strategic 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

• 7-12+ years of experience in enterprise architecture, cloud engineering, or platform leadership.
• 5+ 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.