Strong fundamentals in system design, debugging, and problem-solving
Experience with LLMs in production and deployment at scale
Proficient in Python and familiar with relational databases, ideally PostgreSQL
Hands-on experience with AWS and serverless technologies (Lambda, EC2)
Excellent communication skills to surface blockers and collaborate with stakeholders
Ability to thrive on experimentation and iterate quickly on complex problems
Responsibilities
Design and architect LLM-based systems for processing large volumes of unstructured data
Make key technical decisions in a collaborative team environment
Build systems that extract precise information to support high-stakes insurance decisions
Drive projects from inception to completion while taking full ownership
Engage in rapid experimentation to test and validate innovative ideas
Collaborate with team members to iterate solutions that address tough industry challenges
Communicate proactively to ensure alignment and transparency across the team
Benefits
Significant equity options package
20 days of PTO annually
Global team offsites for bonding and collaboration
100% coverage for PPO medical, vision, and dental for individuals and families
Healthy living/gym stipend and mobile phone bill stipend
Continuing education credits to support professional growth
401(k) plan with employer contribution regardless of employee contribution
Full Job Description
About the role:
Salary range: $222k - $314k USD*
Location: Remote (USA)
We are looking for engineers who enjoy going deep on hard problems and owning end-to-end outcomes. As a Staff engineer on the Submission Processing team, you'll work at the intersection of AI and backend engineering and have major ownership and agency: design the systems, make architectural calls under ambiguity, and play a key role in setting the technical direction for the team.
You'll be working on building and scaling LLM-based systems that process billions of highly unstructured data points on a daily basis, extract precise information, and surface insights that insurers rely on for high-stakes decisions. This is a problem the industry hasn't solved effectively yet, and you'll be working on cutting-edge challenges that require creativity and ambition. We're a small team where individual contributions have an outsized impact on both our technology and our business. You'll be right at home if you:
Have 8+ years of software engineering experience.
Embody hustle and grit, you're excellent at your craft and relentless in pursuing it.
Take full ownership of your work and drive projects to completion with minimal oversight.
Communicate proactively, surfacing blockers, asking the right questions, keeping stakeholders in the loop.
Thrive on experimentation: you're comfortable testing ideas, measuring results, and iterating quickly on problems no one has solved before.
Have strong fundamentals in system design, debugging, and problem-solving.
Have worked with LLMs in production and understand what it takes to deploy them at scale.
Have experience with AWS and serverless technologies (Lambda, EC2), asynchronous workflows, and cloud environments.
Know Python (our main stack), though we're open to strong candidates from other OO backgrounds
Are comfortable with relational databases, ideally PostgreSQL.
Are excited by problems others are struggling with.
Bonus: experience with document pipelines and processing large amounts of data
What you'll get:
Competitive salary (based on experience level)*.
Significant equity options package.
Work with an ambitious, smart, global, and fun team to transform a $7T global industry.
20 days of PTO a year.
Global team offsites.
100% covered PPO medical, 100% covered vision and dental for individuals and families.
Healthy living/gym stipend. Mobile phone bill stipend.
Continuing education credits.
401(k) plan with employer contribution (regardless of employee contribution)
*The salary range listed is an estimate and will vary based on a variety of factors. Final compensation will be determined during the offer stage based on relevant experience, performance during the interview process, and geographic location, and may therefore differ from the posted range.
