- Design, implement, and maintain cloud-native platform to support AI and data workloads, with a focus on AI and data platforms such as Databricks and AWS Bedrock.
- Build and manage scalable data pipelines to ingest, transform, and serve data for ML and analytics.
- Develop infrastructure-as-code using tools like Cloudformation, AWS CDK to ensure repeatable and secure deployments.
- Collaborate with AI engineers, data engineers, and platform teams to improve the performance, reliability, and cost-efficiency of AI models in production.
- Drive best practices for observability, including monitoring, alerting, and logging for AI platforms.
- Contribute to the design and evolution of our AI platform to support new ML frameworks, workflows, and data types.
- Stay current with new tools and technologies to recommend improvements to architecture and operations.
- Integrate AI models and large language models (LLMs) into production systems to enable use cases using architectures like retrieval-augmented generation (RAG).
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