Description

You will build and scale production serving infrastructure for AI and data use cases, moving pilots from prototype to stable release.

This role is on-site.

Responsibilities

• Build serving stores, sync pipelines, and API layers for pilot use cases using Python and FastAPI.
• Configure end-to-end pilot integrations, including source table binding, key schemas, and consumer connections.
• Establish CI/CD pipelines with automated tests for sync correctness, API contracts, and latency benchmarks.
• Operate services to defined SLAs for latency, freshness, and availability.
• Partner with domain teams to onboard use cases and contribute to reference implementations and documentation.

Required Skills

• 5+ years of production Python development with FastAPI or comparable frameworks.
• Experience building and operating batch and real-time data pipelines (Kafka, CDC, or incremental batch).
• Production experience with caching and key-value stores (Redis, Valkey) including invalidation strategies.
• Hands-on experience with vector databases or knowledge graphs (Pinecone, Weaviate, pgvector, Neo4j).
• Production experience with Azure Databricks, Delta Lake, and Unity Catalog, including Delta Lake internals.
• Strong SQL and data modeling skills for point-lookup and analytical query patterns.
• Proficiency with CI/CD tools like GitLab or GitHub Actions for data pipeline automation.

Preferred Skills

• Experience with embedded analytical engines like DuckDB.
• Production experience with Microsoft Fabric, OneLake, or Power BI Semantic Models.
• Experience defining and operating SLAs/SLOs for data products or APIs.

Key Skills

Education

Any Gradute