AI/ML Engineer

Title: AI/ML Engineer (All Levels)Location: Bay Area (Hybrid)Compensation: Up to $350,000 + EquityWe're partnered with a well-funded, high-growth Series B startup building the next generation of AI-native data infrastructure for Fortune 500 enterprises. With 3.5x revenue growth in FY'24 and 160% net revenue retention, they're scaling fast and investing heavily in the AI engineering team that powers their core product.This is a high-impact role where you'll own the intelligence layer of the platform, making real architectural decisions around agent design, model selection, and evaluation strategy. Everything you build ships directly to customers; this is not a POC or internal tooling team.What You'll DoArchitect multi-step AI agents end-to-end, covering problem decomposition, context retrieval, error recovery, and output qualityOwn RAG pipelines, vector and graph-based retrieval systems, and knowledge representations that let agents reason accurately over complex enterprise dataBuild the AI layer behind the platform's core code generation capability, from prompt design and model selection through to fine-tuning and output validationMake production AI work at scale, balancing latency, throughput, and observability, and knowing when to optimize a model versus restructure a systemThink in failure modes and evaluation strategy, not capability demos, and own the improvement loopRequirements4-6+ years of software engineering experience with meaningful AI/ML depthProven experience building and shipping AI agents or coding agents in productionStrong Python skills with hands-on experience across RAG, vector databases, and knowledge graphsExperience with LLM APIs, prompt engineering, fine-tuning, and structured outputs in productionFamiliarity with AWS and Kubernetes for production AI deploymentExperience with data platforms such as Databricks, Snowflake, BigQuery, or Spark is a strong bonusScale or Go experience is a bonusIf you're a builder who thinks in failure modes, owns what you ship, and thrives in environments where last year's best practice is already obsolete, this is a rare opportunity to have direct leverage on a product used by some of the world's largest enterprises.