Role:
Architect the environment. You won't just build pipelines; you'll build the infrastructure that allows ML Engineers and AI researchers to work at speed. Your goal is to make the platform seamless, scalable, and secure.
Key Responsibilities:
- Manage and optimize Databricks clusters and Snowflake instances.
- Implement and maintain infrastructure as code (Terraform/CloudFormation) on AWS.
- AI Infrastructure: Set up and govern AI services like AWS Bedrock, vector databases, and agent-building platforms to empower ML teams.
- Ensure the platform handles high-concurrency workloads and autoscaling requirements.
Must Have:
- Deep expertise in AWS services (S3, EC2, IAM, EKS, Bedrock).
- Experience managing Databricks workspaces and Snowflake administration.
- Strong background in Linux, Docker, and Kubernetes.
Good to Have:
- Apache Iceberg: Hands-on experience implementing Iceberg for storage optimization and cross-tool compatibility.
- Experience with model serving frameworks and LLM gateway configurations.
