Software Engineer - SnowConvert AI

Snowflake is powering the era of the agentic enterprise. The SnowConvert AI team, within the Migrations organization, delivers an AI-driven migration product that moves data-centric applications to Snowflake an order of magnitude faster than industry norms. SnowConvert migrates data, code, ETL pipelines, and BI tools by combining AI-based conversion with execution-level validation, so migrated systems are syntactically correct, semantically equivalent to their source, and production-ready on the Snowflake AI Data Cloud.

Responsibilities

Develop the fundamental code conversion techniques, robust data migration and validation pipelines, and automatic testing components that automated AI agents use to process a complete application migration to Snowflake; Develop the foundations that AI agents rely on for fast, consistent code conversion; Work with the original SnowConvert team, AI team, and FDE team to deliver the architecture; Design APIs carefully for an ever-changing landscape of AI capabilities; Iterate with the FDE team to get quick feedback on prototypes and early products

Requirements

Strong software engineering experience in Python, with a focus on performance, reliability, and distributed systems; Hands-on experience building agentic AI applications, especially in domains such as computer control or code gen; Track record of contributions to open-source agentic frameworks such as LangChain, AutoGen, etc.; Deep understanding of distributed systems, API design, and backend architectures; High agency, meaning ability to take ownership, navigate ambiguity, and independently push projects forward

Nice to have

Experience with GoLang for high-performance backend services; Strong understanding of big data transformation, ETL, and ELT pipelines; Proficiency in Spark, Airflow, dbt, Kafka or other data engineering tools; Familiarity with streaming architectures, event-driven systems, and async processing; Experience optimizing large-scale data pipelines for performance and cost efficiency; Former founding engineers who have built and owned significant technical projects are highly valued