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.

- Solid 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.

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📌 Systems Integration Specialist (Hyderabad)
🏢 NTT DATA Business Solutions
📍 Hyderabad