Software Engineer, AI

At Pylon, we're a small team building a very ambitious product in the mortgage space.

At this early stage, we're looking for an engineer who can see the opportunity of what we're building towards and wants to have a hand in building it.

We're in search of someone who finds difficult problems invigorating and fits well into a high-performing team built on mutual respect and reliance. If you like pushing yourself to learn a massive amount while shipping code that has a huge impact on the end product, Pylon Engineering could be a great place for you.

You'll be a founding member of our AI team, working directly with the CTO to automate mortgage underwriting. Your job is to take complex, open-ended problems and figure out how to solve them—sometimes that means LLMs, sometimes it's a rules engine, sometimes it's a vendor API, and sometimes it's just good code.

Mortgage underwriting involves hundreds of discrete verification, compliance, and validation steps. You'll be tackling these sub-problems one by one—each is greenfield and requires different technical approaches. You'll define the approach, architect the solution, write a significant portion of the code yourself, and ship it to production. As the team grows, you'll determine how to split up the work and set technical direction.

This isn't a pure ML role—we're not training models from scratch. It's also not about integrating off-the-shelf APIs. It's about having strong technical judgment to pick the right tool for each problem, then building production systems that work in a regulated environment.

You'll be hands-on from day one. Week one includes taking an underwriter certification course to deeply understand the domain you're automating. You'll work in our existing mortgage engine codebase, building new automation services that integrate with the platform.

Strong systems engineering foundation

• You've built large-scale production systems at high-caliber technology companies

• You write code that others can maintain and build on

• You understand distributed systems, APIs, data consistency, and operational excellence

• You've made consequential architectural decisions and lived with the results

Recent AI/ML product experience

• In the past 1-2 years, you've worked on a product that uses LLMs or ML in production

• You understand when AI is the right tool and when it's not

• You've dealt with the reality of prompt engineering, model evaluation, or integrating third-party AI services

• You don't need to have trained models yourself, but you need to have shipped AI-powered features to users

Technical judgment across problem spaces

• You can look at a problem and know whether it needs an LLM, optimization algorithm, rules engine, or just solid code

• You're comfortable evaluating build vs. buy decisions and vetting third-party tools

• You've worked on problems where the right solution wasn't obvious from the start

Comfort with regulated domains

• Ideally you've worked in fintech, healthtech, or another regulated space

• You understand that moving fast doesn't mean breaking things

• You can absorb complex domain knowledge and apply it to technical decisions

Hands-on execution

• You build systems yourself, not just design them—you'll be writing ~50% of the time

• You can take an ambiguous goal and turn it into a working system

• You're the founding member of the team, so there's no one else to delegate to initially

• Job title: Staff Engineer, AI

• Location: Palo Alto, CA

• Stock options: own a piece of the company and we all win together

• Health insurance, 401K, dental, etc.

We don't require that you've worked with any of these technologies before, this is just our stack for your information:

• Languages: Type Script (primary), with flexibility for the right tool per problem

• Data: PostgreSQL

• Infrastructure: AWS

You:

Have strong opinions that you're willing to defend. We have a culture of vigorous discussion and debate on technical decisions. We'll push you to defend your choices, and we want you to push back.

Don't settle. Challenge yourself to frequently and consistently deliver exceptional code. If something could be better, take the initiative to…