Developer Associate - Cortex Code Enablement at Snowflake · Menlo Park

Summary: Snowflake is a company focused on mobilizing the world’s data, seeking a Developer Associate to enhance their Cortex Code platform. The role involves creating documentation, running events, and collaborating with teams to drive adoption and enablement of AI-powered development tools. Responsibilities: - Own the Cortex Code enablement experience end-to-end, from onboarding content and quickstarts to advanced how‑to guides and best practices for data engineers, analysts, and developers - Define and maintain documentation, tutorials, and samples for Cortex Code, including: - Product overviews and conceptual docs - Step‑by‑step guides and walkthroughs - Code examples and reference projects - “How we built this” patterns for data and AI workflows - Design, launch, and run hackathons, workshops, and events (internal and customer-facing) that showcase Cortex Code capabilities and drive meaningful adoption - Create and curate Agent Skills for Cortex Code, working closely with engineering, Product Managers, and solution architects/engineers to: - Identify high‑value use cases and workflows - Design skill specifications and behaviors - Iterate based on usage data, evaluation results, and user feedback - Collaborate with GTM and field teams (sales, SEs, partners, marketing) to build collateral and enablement: - Battlecards, demos, and solution briefs - Customer-ready decks and walkthroughs - Playbooks for common patterns (e.g., dbt, Airflow, data quality, governance) - Represent the voice of AI‑native builders by synthesizing feedback from customers, community, and internal users into prioritized product and skills roadmaps - Measure impact of enablement assets and events using adoption, engagement, and performance metrics; use these insights to continuously refine content, skills, and programs Required Qualifications: - Completion of a Bachelor's or Master's degree in Computer Science, Engineering, AI/ML, Data Science, Human‑Computer Interaction, or a related technical field - Demonstrated product mindset through internships, projects, or leadership in: Developer tools, data platforms, or productivity products, and/or Building, shipping, or maintaining AI-powered applications - Strong technical foundation with the ability to understand and explain: How LLMs work at a high level (prompting, tokenization, grounding, evaluation), Common AI patterns like RAG, tools/agents, and function calling, Data and analytics workflows (SQL, ELT/ETL, dbt, orchestration tools like Airflow) - AI‑native experience, such as: Building projects using LLM APIs (e.g., OpenAI, Anthropic, Snowflake Cortex, OSS models), Designing prompts, tools/skills, or agents to solve real‑world problems, Experimenting with model evaluation, safety/guardrails, or latency/cost tradeoffs - Excellent communication and storytelling skills: Able to translate complex AI and data concepts into clear documentation, diagrams, and examples, Comfortable presenting in workshops, hackathons, and community events - Bias for action and ownership – you enjoy starting from a blank page, structuring ambiguous problems, and iterating quickly based on feedback and data - Strong collaboration skills, with experience working across engineering, design, PM, and go‑to‑market teams (from school projects, internships, or prior roles) Preferred Qualifications: - Prior experience as a software engineer, data engineer, or ML/AI engineer (internships, co‑ops, or substantial personal projects) - Experience with: Snowflake or other cloud data platforms or similar data workflow tools, Building internal tools, bots, or plugins that integrate LLMs with existing systems - Contributions to open-source projects, technical blogs, or developer communities (meetups, Discord/Slack communities, forums, etc.) - Experience organizing hackathons, meetups, or student clubs focused on AI, data, or developer tools Required Skills: Developer tools, Data platforms, AI-powered applications, Large Language Models (LLMs), Prompt engineering, Tokenization, Grounding, Evaluation of AI models, Retrieval-Augmented Generation (RAG), AI tools, agents, Function calling, Data analytics workflows, SQL, ELT/ETL, dbt, Orchestration tools (Airflow), LLM APIs OpenAI, LLM APIs Anthropic, LLM APIs Snowflake Cortex, LLM APIs OSS models, Prompt design, AI model evaluation, Safety, guardrails in AI, Latency, cost tradeoff analysis, Bias for action Benefits: Medical, dental, vision, life, and disability insurance, 401(k) retirement plan, Flexible spending & health savings account, At least 12 paid holidays, Paid time off, Parental leave, Employee assistance program, Other company benefits