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. + Robust 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.

📌 Systems Integration Specialist (Hyderabad)
🏢 NTT America
📍 Hyderabad