Staff AI Engineer - Cortex Code Quality

Responsibilities

• Own major pillars of the quality stack: tuning agent behavior to engage on next generation agentic coding tasks.
• Design and evolve pipelines and tooling that support large-scale experimentation, error mining, and iteration on prompts/tools/workflows with clear before/after signals.
• Lead postmortems on quality regressions; cluster failure modes; translate findings into a prioritized roadmap for engineering and modeling partners.
• Align product, infra, and applied AI on what “good” means for critical customer workflows; mentor engineers and uplevel eval craft across the team.
• Ensure quality systems are dependable in practice—reproducible runs, stable datasets, versioning, and operational clarity when things drift.

Requirements

• Bachelor’s degree in Computer Science, Engineering, Statistics, or a related field. Master’s or higher preferred but not a requirement.
• 8+ 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 writeups, constructive debate, and ability to influence without authority across engineering and product.

Nice to Haves

• Experience with data engineering pipelines (dbt, Airflow), data modeling, data analysis, retrieval systems, and semantic layers.
• 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.
• Prior work on LLM observability, safety/guardrails, or quality systems used as release gates in production.