> Markdown version of [/jobs/ext/2512938-senior-staff-agent-platform-cortex-code](https://www.wearedevelopers.com/jobs/ext/2512938-senior-staff-agent-platform-cortex-code). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior/Staff - Agent Platform (Cortex Code) - **Company:** Snowflake Inc. - **Location:** Menlo Park, CA, United States - **Experience:** Expert - **Salary:** $236,000.0 - $309,750.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Data Analysis, ARM Architecture, Automated Storage and Retrieval Systems, Information Engineering, Python (Programming Language), TypeScript, Management of Software Versions, Large Language Models, Data Layers, Information Technology, Data Pipelines, Golang - **Published:** August 12, 2026 - **Apply:** https://diversityjobs.com/main/sendform/8/8/28176/1/17906984?backUrl=%2Fcareer%2F17906984%2FSenior-Staff-Agent-Platform-Cortex-Code-California-Menlo-Park ## About the Role * Bachelor's degree in Computer Science, Engineering, Statistics, or a related field. Master's or higher preferred but not a requirement. * 10+ years of experience shipping AI/ML-backed software in production, including Staff-level ownership of technical direction, cross-team delivery, and mentoring. * Strong track record building and operating eval harnesses, measurement, and/or experimentation loops for LLM/agent systems-not only one-off benchmarks. * Proficiency in programming languages such as Python, TypeScript, Go (strong in at least two). * Exceptional communication skills: crisp write-ups, constructive debate, and ability to influence without authority across engineering and product. * (Optional) Experience with data engineering pipelines (dbt, Airflow), data modeling, data analysis, retrieval systems, and semantic layers is a plus. Nice to have * Deep experience with agentic coding tools (IDE agents, CLI agents) and intuition for model strengths, failure modes, and prompting limits. * Background in data engineering (dbt, Airflow), analytics, retrieval / RAG, or semantic layers-highly relevant for data-centric coding agents. * Prior work on LLM observability, safety/guardrails, or quality systems used as release gates in production. ## Description The Cortex Code team is building the future of coding agents for working with data. See our flagship product in action: Cortex Code in Action: Live Demos + AMA., * Agent strategy & systems: Own major pillars of the quality stack: tuning agent behavior to engage on next generation agentic coding tasks. * Hill-climb infrastructure: Design and evolve pipelines and tooling that support large-scale experimentation, error mining, and iteration on prompts/tools/workflows with clear before/after signals. * Deep analysis & prioritization: Lead postmortems on quality regressions; cluster failure modes; translate findings into a prioritized roadmap for engineering and modeling partners. * Cross-functional leadership: Align product, infra, and applied AI on what "good" means for critical customer workflows; mentor engineers and uplevel eval craft across the team. * Production-minded rigor: Ensure quality systems are dependable in practice-reproducible runs, stable datasets, versioning, and operational clarity when things drift., * Have built and owned complex quality + data pipelines-substantial state, branching logic, and operational requirements. * Thrive in high-intensity environments with short feedback loops and high standards for rigor. * Take ambiguous "quality is slipping" problems to completion: you care about clear metrics, reproducibility, and sustained improvement-not one-off score bumps. * Are a power user of modern coding agents and care about turning intuition into systematic measurement and team-wide practice. ## Related Videos - [Building a Multi-Agent Orchestration Engine That Actually Follows the Rules](https://www.wearedevelopers.com/videos/100159-building-a-multi-agent-orchestration-engine-that-actually-follows-the-rules) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Go with the Flow: Stop the Leaks Before Your Memory's a Waterfall!](https://www.wearedevelopers.com/videos/100073-go-with-the-flow-stop-the-leaks-before-your-memory-s-a-waterfall) - [Do TypeScript without TypeScript](https://www.wearedevelopers.com/videos/327-do-typescript-without-typescript) - [On a Secret Mission: Developing AI Agents](https://www.wearedevelopers.com/videos/1510-on-a-secret-mission-developing-ai-agents) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) ## Related Articles - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [What is Agentic Programming and Why Should Developers Care?](https://www.wearedevelopers.com/magazine/625-what-is-agentic-programming-and-why-should-developers-care) - [A 5-Step Open-Source Setup for Agentic Engineering](https://www.wearedevelopers.com/magazine/738-a-5-step-open-source-setup-for-agentic-engineering) - [Everything a Developer Needs to Know About MCP with Neo4j](https://www.wearedevelopers.com/magazine/604-everything-a-developer-needs-to-know-about-mcp-with-neo4j) - [Never delegate the understanding](https://www.wearedevelopers.com/magazine/749-never-delegate-the-understanding)