Design and build data-driven tools that operate on large datasets stored in S3 and Snowflake
Implement pipelines that:
Extract specific columns or datasets from Snowflake
Generate vector embeddings via APIs such as OpenAI
Store and manage embeddings in vector databases like Pinecone
Enable semantic search and similarity-based retrieval
Develop enrichment workflows that:
Query structured data
Use LLM APIs to generate new derived columns
Write enriched results back into Snowflake
Build reusable internal services and SDKs around embedding generation, prompt orchestration, and data augmentation
Optimize performance and cost across AWS infrastructure
Work closely with product and data teams to turn use cases into scalable engineering solutions
Ensure reliability, observability, and maintainability of AI-powered pipelines

5+ years of software engineering experience
Strong backend engineering skills (Python preferred; other modern languages acceptable)
Solid experience with:
AWS (IAM, Lambda, ECS/EKS, S3, networking, security best practices)
Data warehousing (Snowflake preferred)
API design and distributed systems
Hands-on experience working with LLM APIs (e.g., OpenAI) and embedding workflows
Experience with vector databases (Pinecone or similar)
Strong understanding of data modeling, ETL/ELT patterns, and performance optimization
Production experience in at least one startup environment
Ability to operate independently and ship high-impact systems end-to-end

Senior Data & AI Platform Engineer, AWS, Snowflake, Vector Search

Key skills