ZipBuilds what the customer runs
Software Engineer, Forward Deployed (Mid - Senior Level)
San Francisco, CAHybrid
$150,000–$250,000
Updated
$175,000–$225,000San Francisco, CA
Product Engineer responsible for rapidly shipping customer-facing software, integrations, and reliable workflows for property management customers.
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$175K–$225KAbove the median
Median $190K
This job$175K–$225KTypical senior FDE payMiddle 50% of 1,789 postings$160K–$220KBuilds what the customer runs
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Posted by Two Dots on
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.
We’re hiring a Product Engineer to help us build practical, customer-facing software quickly and well.
This is a role for future founders and people who have a deep sense of ownership over customer outcomes and creating tangible value quickly. It’s a hybrid product, engineering, and customer-facing role for career software engineers that think like a business operator. You’ll work closely with product, engineering, customer teams, and sometimes directly with customers to ship the software that makes Two Dots more useful, more reliable, and easier to adopt.
Examples of work might include converting manual onboarding steps to self-service, integrating with property management systems to generate revenue, or quickly solving urgent customer workflow issues, either from the office or on-site with the customer.
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.
The best person for this role is grounded, realistic, and impact-oriented. They want the business to succeed, customers to get value, and the product to become easier to adopt.
They do not need an elite CS background or large-scale systems specialization. They do need to be a strong enough engineer that they can ship independently without creating quality-control burdens for the rest of the team.
They are fluent with modern coding agents and AI-assisted development, but they do not outsource their judgment. They understand the code they change, recognize when they are taking on technical debt, and make those tradeoffs deliberately.
They are also comfortable with scope, structure, and team goals. They understand that startups are not a license to “do whatever I want”, they are an opportunity to work with urgency and ownership toward important outcomes where your contribution matters greatly.
We evaluate candidates most heavily on judgment, communication, self-management, teamwork, and ability to deliver customer outcomes without creating unnecessary debt. Technical skill matters, but this is a product delivery role first.
AI underwriting agent ("Eve") that automates income verification, identity checks, and fraud detection for multifamily property managers screening rental applicants.
Series A · 10–50 people
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San Francisco, CAHybrid
$150,000–$250,000
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