Python Developer

Job Title: Full-Stack Engineer – Snowflake & Cortex AI

About the Role

We’re looking for a hands-on full-stack engineer who can turn Snowflake’s data infrastructure into intelligent, conversational products. You’ll own end-to-end delivery of chat-based applications that surface both structured and unstructured data stored in Snowflake, leveraging the latest Snowflake Cortex AI capabilities (Cortex Analyst, Cortex Search, and Cortex Agents).

What You’ll Do

• Design & build chatbots that access, reason over, and summarize Snowflake data sets (tables, documents, and semi-structured data).

• Develop full-stack features (frontend, backend, and DevOps) to deliver secure, scalable conversational experiences.

• Integrate Snowflake APIs & Cortex AI components—implement vector search, retrieval-augmented generation (RAG), and agent workflows.

• Model, transform, and optimize data pipelines to make information chatbot-ready (tokenization, embeddings, prompt engineering).

• Establish engineering best practices around code quality, CI/CD, observability, and automated testing for AI-powered services.

• Collaborate cross-functionally with data engineers, data scientists, and product managers to iterate quickly from concept to production.

• Stay current on Snowflake product releases, LLM advances, and GenAI safety/ethics guidelines; evangelize learnings within the team.

Must-Have

5+ years building production full-stack applications (any modern JS/TS framework + backend language).

Demonstrated expertise with Snowflake SQL, warehousing concepts, and Snowflake APIs/Snowpark.

Hands-on work with Snowflake Cortex (Analyst, Search, Agents) or clear evidence you can ramp up fast.

Solid grasp of REST/GraphQL, authentication (OAuth/JWT), and cloud infrastructure (AWS, Azure, or GCP).

Ability to write clean, test code and perform code reviews.

Nice-to-Have

Experience fine-tuning or deploying LLMs (OpenAI, Anthropic, etc.).

Familiarity with Lang Chain, LlamaIndex, or similar RAG frameworks.

Experience with real-time streaming (Kafka, Snowpipe) and event-driven architectures.

Knowledge of UI/UX patterns for conversational interfaces (chat widgets, voice, etc.).

ML/DS background or academic work in NLP / IR.