Python (3.11+): Hands-on experience building robust applications and agentic logic.
Amazon SageMaker Unified Studio (SMUS) & MLOps: Hands-on experience with SMUS to manage the end-to-end ML lifecycle. This includes automating model training, registering models in the centralized registry, and configuring real-time/asynchronous inference endpoints within the SMUS ecosystem.
Infrastructure as Code (IaC):Production-level expertise using Terraform to provision AWS services, including Bedrock Agents, Knowledge Bases, DynamoDB, Lambda, etc.
CI/CD & DevOps: Proven track record in building and maintaining automated deployment pipelines for cloud-native applications and MLOps workflows.
Skills:
AWS Lambda, Amazon Web Services (AWS), Ecosystems, Knowledge Base
Virtusa Corp
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