Vice President, Engineering

Doma

VP of Engineering at Doma Technology overseeing engineering platform end to end. Leading a team and building real time decision engine that enhances customer satisfaction.

Posted 7/18/2026full-timeRemote • California • 🇺🇸 United StatesLead💰 $280,000 - $340,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive experience in leading engineering teams and delivering production systems in regulated financial environments, with a strong focus on machine learning and data infrastructure. Capable of driving engineering velocity while ensuring reliability and alignment across cross-functional teams.

Highest-signal resume keywords

8+ Years Engineering ExperienceAI/ML Production SystemsFintech/Proptech/Insurtech ExperienceData Infrastructure SolutionsTeam Leadership in Startup Environments

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningData IngestionSoftware DevelopmentRisk ModelingProduction System DeploymentData ScrapingAutomationEngineering Process OptimizationDecision Engine DevelopmentRegulatory Compliance

Soft Skills

CommunicationTeam AlignmentOwnershipProblem SolvingLeadership

Industry Keywords

FintechProptechInsurtechReal Time Decision EnginePublic RecordsAutomated ProcessesCEO ReportingStartup Growth StageAmbiguous Problem SolvingFragmented Records

About the role

Key responsibilities & impact

own our engineering platform end to end
partner closely with data science and machine learning to build and scale the real time decision engine
lead a team of 10+ engineers based in the Bay Area
report directly to the CEO
measure success by how much faster, more reliable, and automated processes become
replace manual, paper based review processes with software by ingesting messy public records, documents, and outside data
apply proprietary risk models built on 100,000+ policies
ship a production system already approved by Fannie Mae and live in real mortgage transactions

Requirements

What you’ll need

8+ years of engineering experience, including leading and scaling a team of 10 or more engineers
AI/ML platforms: you've shipped production systems that rely on machine learning or agentic automation, not just prototypes
Regulated, financially significant transactions: fintech, proptech, or insurtech experience where your software plugged directly into a customer's financial decision
Startup environments: Series A through growth stage, where you've operated with little direction and owned ambiguous problems end to end
Ownership: comfortable owning a platform end to end and reporting directly into the CEO
Technical depth: able to go deep with data science and ML partners on the core decision engine, not manage from a distance
Data infrastructure: experience solving real world problems around fragmented records, scraping, ingestion, and reliability at scale
Velocity: can materially increase engineering speed without sacrificing reliability in a regulated industry
Communication: can align a small, senior team around a fast moving roadmap and keep data science, ML, and engineering in sync

Benefits

Comp & perks

medical/dental/vision insurance
401(k)
generous vacation time
paid bonding leave