Applied AI Engineer

Join Pulley, a company focused on revolutionizing the permitting process. As a Senior AI Engineer, you will be responsible for building AI-powered features, turning unstructured permitting documents into structured outputs, and establishing a foundation for evaluating and observing LLM-powered features. You will also make technical and product decisions that directly impact customers and their projects, and raise the bar for engineering standards within the team.

You’re product-minded: you care whether the thing you built actually solved the customer’s problem, and you’ll talk to users to find out

Responsibilities

• Own AI-powered features end-to-end, from user interaction to deployment and iteration in production.
• Turn unstructured permitting documents and regulations into structured, reliable outputs through extraction, classification, and retrieval.
• Build the evaluation and observability foundation to measure quality and regressions, ensuring confidence in LLM-powered features.

Requirements

• You default to ownership: when something is broken or missing, your instinct is to fix it, not to file it as someone else’s problem
• You have strong opinions about quality and velocity and don’t treat them as a tradeoff—you look for the tools, abstractions, and processes that buy both
• You thrive in ambiguity—you’d rather define the right problem than execute a spec, and you’re energized rather than paralyzed when the path isn’t laid out
• You’re rigorous about what “working” means—you don’t trust a demo, you trust an eval, and you build the measurement before you build the feature
• Track record of owning an LLM-powered product surface end-to-end: requirements through production, including the unglamorous parts—data quality, eval design, cost and latency, failure handling
• 4+ years of software engineering experience, with a substantial portion building production LLM or ML systems
• Ability to architect durable systems while making pragmatic tradeoffs
• Real experience building with AI coding agents—not just autocomplete; you’ve shipped work where agents did substantial implementation under your direction
• Deep hands-on experience with large language models in production—prompting, retrieval-augmented generation, structured extraction, tool use and agentic workflows, and knowing when each is the wrong tool
• Based in the San Francisco Bay Area and willing to work in person 4 days a week
• Experience designing evals and otherwise making LLM-powered features reliable in production
• Experience with document understanding at scale—OCR, layout-aware parsing, or vision-language models over scanned PDFs, drawings, or forms
• Experience in construction tech, govtech, proptech, or another domain where the hard part is messy real-world documents and processes
• Experience with modern full-stack development—we use TypeScript, React, and Google Cloud—and an appetite for working in the application code that puts AI features in front of users
• Startup experience at the stage where you helped build the team, not just the product
• Experience mentoring engineers or leading technical direction across teams

Preferred

• Experience fine-tuning models or building data pipelines to produce training and eval sets from real-world usage

Pay

USD 230,000 - 350,000