USD per year
Integrations Engineer
Location
San Francisco HQ
Employment Type
Full time
Department
Engineering
Compensation
- $175K – $250K • 0.1% – 0.5%
Company Mission / Why This Matters
Two Dots builds verification and risk infrastructure for housing to help solve the housing crisis. Housing is too expensive because America created a single family mortgage machine to cut average people into home price inflation fueled by soft bans on new development. That worked for many decades, but when a small single family home costs several million dollars, it stops being an engine of opportunity and becomes a source of the very resentment modern mortgages were originally created to solve. Housing supply has been restricted so much that people have started fabricating documentation or relying on bypasses and overrides to sign up for a payment they can’t really afford. That conceals the problem instead of solving it. We believe that public and private policy has to change, and that involves breaking the system that conceals our affordability crisis and leaves people without the disposable income required to live satisfying lives, fueling resentment and political instability that turns problems at home into problems for the world.
Role
We are looking for an engineer to own critical ERP integrations. You will use agents to discover API behavior, make codebase-wide changes that isolate and unify integration points, and turn unreliable third-party APIs into highly reliable integrations. You will also build browser extensions for other apps with minimal QA guidance, where extreme attention to detail and defensive programming matter because extensions are hard to update quickly. This role works closely with customers, sales, customer success, and other engineers. You should know when an integration seam requires changing the product itself rather than creating a forever workaround. Integrations directly determine our total addressable market, so your work will be tied to major revenue and company value changes. You should have strong Python and JavaScript skills, understand relational databases, ideally Postgres, and be comfortable with queues and durable asynchronous workflows. We expect experience with messy integrations, scrapers, bidirectional syncing, or similar systems.
The Team
Henson (CEO) started his career selling FX derivatives to hedge funds at Goldman, then worked at a real estate tech startup for several years leading sales. This enables him to engage with the largest institutional property managers and real estate investors in the country and create value through those relationships. Max (CTO) started out as a software engineer at Blend, a mortgage application company that went public, and went on to work on the search team at Google. That combination of specific consumer fintech experience and knowledge of how sophisticated ML products succeed in production made big enterprise deals work from day 1. We met in middle school and created a media website together where people could watch and post their flash games and animations. We learned to code, source talent, and forge partnerships - and had 500 active users. Although a tragic addiction to World of Warcraft interrupted work on the website, we got back together to start Two Dots. Other team members include: Meta ML alumnus with decades of experience, a 21 year old UMich grad who was a top 2,000 LoL player (he is no longer playing the game, thank god), and a former agave farmer who started a shipping and logistics company while at Stanford.
About the interview
1. Initial introduction call / alignment on what the role is: 15 minutes
- Coding screener that involves dealing with a failure-prone service
- Behavioral phone screen
4. Onsite interview with multiple stages, including a coding agent session to discover an API, system design, behavioral elements Compensation Range: $175K - $250K
Two Dots unlocks unstructured financial documents to enable smarter financial decisions by automating underwriting and screening processes. Their intelligent software helps clients cut overheads, eliminate risk, and provide faster decisions that win the best applicants.
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