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.
•
Robust 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.
•
📌 Systems Integration Specialist (Hyderabad)
🏢 NTT
📍 Hyderabad