Must Have

• 5–7 years of cloud engineering experience with 3+ years focused on AI/ML platforms

• Deep hands-on expertise with AWS AI/ML services: SageMaker (training, pipelines, inference, JumpStart), Bedrock

• Deep hands-on expertise with Azure AI/ML services: Azure Machine Learning, Azure OpenAI, Azure AI Foundry

• Experience building MLOps platforms and automated ML pipelines

• Strong knowledge of LLMOps, LLM lifecycle management, agentic AI, RAG (retrieval-augmented generation), and prompt engineering

• Experience implementing guardrails and governance for LLM services

• Proficiency in Python and infrastructure-as-code (Terraform, CloudFormation, ARM/Bicep)

• Experience with MLflow (or similar tool), experiment tracking, and model registries

• Expertise in cloud security patterns including private endpoints, customer-managed keys, and network isolation for AI/ML services

• Strong understanding of cloud networking architecture in regulated environments

• Experience working in highly regulated industries with compliance requirements

• Agile delivery experience.

Nice to Have

• AWS or Azure AI/ML certifications

• Experience with vector databases and embedding models

• Knowledge of model optimization and inference acceleration

• Background in financial services or banking

Senior Cloud Engineer – AI/ML Platform