Lead the architecture, design, and governance of enterprise-scale AI/ML platforms across AWS, Azure, and GCP. Responsible for AI infrastructure, MLOps, GPU platforms, security, governance, and cloud strategy.
Key Responsibilities
AI/ML Infrastructure
- Design infrastructure for:
- Model Training
- Fine-Tuning
- Inference
- Monitoring
- Build GenAI and LLM-based platforms.
- Define reusable AI reference architectures.
Multi-Cloud Architecture
- AWS:
- SageMaker
- EKS
- EC2 GPU
- S3
- IAM
- Azure:
- Azure ML
- AKS
- Azure OpenAI
- GPU VM Series
- GCP:
- Vertex AI
- GKE
- TPU/GPU Infrastructure
MLOps & Platform Engineering
- Establish CI/CD for ML.
- Design:
- Model Lifecycle Management
- Continuous Training
- Deployment Automation
- Drift Detection
- Observability
- AI Security Architecture
- Identity & Access Management
- Responsible AI Controls
- Compliance & Governance
Leadership
- Technical leadership for AI initiatives.
- Mentor architects and engineering teams.
- Support cloud strategy and platform roadmaps.
- Engage executive stakeholders.
- CI/CD for ML
- Model Registry
- Experiment Tracking
- Monitoring & Logging
Data Platforms
- Distributed Systems
- Streaming Architecture
- Batch Architecture
Preferred Qualifications
- Bachelor's/Master's degree in Computer Science or Engineering.
- Experience building enterprise AI platforms at scale.
- Solid exposure to Responsible AI and Governance.
- Experience in cloud cost optimization and client-facing consulting roles.
📌 AI infra Architect (Chennai)
🏢 LTM
📍 Chennai
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