Staff AI Engineer

Pulley; San Francisco (CA); Hybrid; USD 300,000 - 350,000; Full time

Benefits offered by this job

Competitive compensation

Meaningful equity

Health & dental insurance

In-person and remote work options

401(k)

Job summary

Pulley is seeking a Staff AI Engineer to lead end-to-end AI product work, shaping the technical direction for LLM applications across multiple surfaces. You will own complex, messy inputs and transform them into fast, structured outputs, with a focus on reliability and production readiness.

Based in the San Francisco Bay Area, you will mentor engineers, define evaluation standards, and drive architecture decisions for agent-driven workflows, aiming to accelerate permitting processes and reduce

Qualifications

• 8+ years of software engineering experience, with a substantial portion building production LLM or ML systems.
• Track record of owning a significant AI domain end-to-end: from problem to production ownership, including data quality, eval design, cost and latency, failure handling.
• Deep hands-on experience with large language models in production—prompting, retrieval-augmented generation, structured extraction, tool use and agentic workflows.

Responsibilities

• Own the AI problem space—define the technical direction for how Pulley applies LLMs across multiple product surfaces, and carry it from ambiguity through architecture to shipped product.
• Turn unstructured permitting documents, city regulations, and jurisdiction workflows into structured, reliable outputs—extraction, classification, retrieval, and agentic workflows.
• Set the evaluation and observability standard for the company: define ground truth, measure quality and regressions, and build the systems that ensure model improvements are adopted.
• Build with AI agents as a daily practice—directing, reviewing, and shipping agent-driven work at high velocity while maintaining quality.
• Make the technical bets for next year—models, architectures, and what to build vs. buy—and own those outcomes in production.
• Multiply engineers by setting patterns, mentoring toward larger scope, and accelerating team speed through systems and standards.

Job description

We're building the infrastructure that takes permitting from months to days. Join a team of engineers, permitting experts, and operators solving one of construction's hardest problems.

what guides us

Our values

Our values are an essential part of how we operate. They shape every aspect of life at Pulley, including how we relate to our customers, our colleagues, and our work.

Quick

Urgency and a bias to action. We keep feedback loops tight, favor progress over perfection, and move fast without being careless.

Kind

Empathy, warmth, and honest feedback. We assume positive intent — but kind doesn't mean soft.

Crafty

Quality of work and clever problem-solving. We're precise and inventive — not sneaky or corner-cutting.

life at pulley

Built for people
who build.

We believe great work happens when people have autonomy, context, and trust.

We're a small, focused team where every person's contribution is visible. If you want ownership, speed, and the chance to build something that matters you'll fit right in.

• Competitive salary and meaningful equity
• Comprehensive health, dental, and vision insurance
• Opportunities for in-person and remote work
• Flexible PTO
• 401(k)

open roles

Join the team

We're hiring across every team. If you don't see a perfect fit, reach out anyway — we're always looking for exceptional people.

Location

Employment Type

Full time

Department

Compensation

About Pulley

Pulley helps the country’s top architects, builders, and retailers speed up every project in their portfolio. With AI-powered permitting intelligence and expert guidance, we eliminate costly delays and bring predictability across the full lifecycle of commercial projects.

Today, permitting is the slowest, most uncertain part of building, spread across 19,000+ jurisdictions with different rules, timelines, and surprises. Pulley gives project teams the clarity and predictability they need to move from planning to opening without delays.

We support rollout programs for brands like J.Crew, Solidcore, and Hibbett Sports, as well as major data center buildouts, EV charging networks, and other commercial projects. Our platform dramatically reduces approval timelines, improves forecasting accuracy, and removes thousands of hours of manual work from design and construction teams.

Founded in 2021, Pulley combines deep permitting expertise with purpose-built AI from people who have created products used by millions. We’re backed by CRV, Susa Ventures, Fifth Wall, and leaders from Plaid, Segment, ServiceTitan, and Procore.

WHAT YOU’LL DO

In this role, you will build the intelligence behind the product that gets stuff built. Permitting runs on messy inputs—scanned plan sets, jurisdiction code, reviewer comments, application forms that differ in every city—and turning that into something fast, structured, and trustworthy is the core technical problem at Pulley. As a staff-level AI engineer, you will:

Own the AI problem space, not just features—define the technical direction for how Pulley applies LLMs across multiple product surfaces, and carry it from ambiguity through architecture to shipped, iterated-on product

Turn unstructured permitting documents, city regulations, and jurisdiction workflows into structured, reliable outputs—extraction, classification, retrieval, and agentic workflows over documents that were never designed to be machine-readable

Set the evaluation and observability standard for the company: decide how we define ground truth, measure quality and regressions, and know when a model change is actually an improvement—and build the systems that make that the default for every team shipping LLM features

Build with AI agents as a daily practice—directing, reviewing, and shipping agent-driven work at high velocity while owning the quality bar

Make the technical bets that determine what Pulley can build next year, not just this quarter—which models, which architectures, what we build versus buy—and own the consequences of those bets in production

Multiply the engineers around you: set the patterns others build LLM features within, mentor senior engineers toward larger scope, and make the whole team faster through the systems, standards, and abstractions you create

WHO YOU ARE

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

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 default to ownership at organizational scale: when something is broken or missing—a system, a process, a gap between teams—your instinct is to fix it, and you don’t need permission or a mandate to start

NEED TO HAVE

8+ years of software engineering experience, with a substantial portion building production LLM or ML systems

Track record of owning a significant AI domain end-to-end: from “this is somebody’s problem” through architecture, delivery, and production ownership, including the unglamorous parts—data quality, eval design, cost and latency, failure handling

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

Experience designing evals and otherwise making LLM-powered features reliable in production

Real experience building with AI coding agents—not just autocomplete; you’ve shipped work where agents did substantial implementation under your direction

Ability to architect durable systems while making pragmatic tradeoffs

Experience mentoring engineers or setting technical direction that other engineers built within

Based in the San Francisco Bay Area and willing to work in person 4 days a week

NICE TO HAVES

Experience with document understanding at scale—OCR, layout-aware parsing, or vision-language models over scanned PDFs, drawings, or forms

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

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

Experience as the most senior AI engineer in a domain—being the person others escalated to when nobody knew the answer

Startup experience at the stage where you helped build the team, not just the product

Compensation Range: $300K - $350K