Founding Software Engineer - Data Platform
Arlo is rebuilding health insurance from the ground up using AI. The healthcare experience today is expensive, confusing, and often so frustrating that people delay the care they need. We’re changing that by reimagining what a health plan should be: a proactive partner that enables health rather than denying it. Our AI-native platform delivers continuous, personalized support for members—helping them navigate benefits, schedule appointments, access high-quality care, and avoid financial fear. Powered by the industry’s most advanced risk-pricing engine, Arlo is already scaling fast: we’ve grown to $XXXM in premiums, cover tens of thousands of people, and see accelerating demand across brokers, employers, and partners. Backed by Upfront Ventures, 8VC, and General Catalyst, our team combines deep industry expertise (Palantir, YC) with the ambition to modernize a $1T market.
About the Role
As the Founding Software Engineer on our Data Platform team at Arlo, you will build the foundation for our ML-driven health insurance quoting system. You'll design and implement the entire data infrastructure that powers our core product, working at the intersection of data engineering and machine learning operations.
What You Will Do
Design and build scalable data pipelines that process billions of healthcare claims records
Develop robust ETL workflows to ingest, normalize, and transform medical data from multiple sources
Create infrastructure for real-time ML inference serving hundreds of millions of predictions
Build developer tooling to accelerate the work of our data scientists and ML engineers
Architect and implement monitoring systems to ensure data quality and model performance
Optimize PySpark code for feature construction to improve performance and efficiency
Projects You Will Work On
Healthcare Data Platform:
Build a unified data platform that ingests medical data from diverse sources and normalizes it for both training and inference
Develop workflow orchestration tools to automate complex data processing pipelines
Create CI/CD pipelines for reliable deployment of data transformations and ML models
Refactor and optimize existing PySpark code to enhance performance and scalability
ML Production Infrastructure:
Design and implement real-time inference systems that can handle high-volume prediction requests
Build infrastructure for A/B testing and controlled model rollouts
Develop monitoring tools to track model performance and data drift in production
This role combines data engineering and ML infrastructure expertise to create the backbone of our AI-powered health insurance platform. You'll work across the full ML lifecycle, from initial data processing to production deployment and monitoring.
What We are Looking For
3+ years of experience as a backend engineer, data engineer, or software engineer with exposure to data pipelines and large-scale infrastructure.
Strong understanding of data structures, algorithms, and scalable system design.
Demonstrated ability to design secure, robust, and scalable infrastructure for data and backend systems.
Hands-on experience with big data tools (e.g., Spark) and pipeline orchestration platforms (e.g., Dagster, Airflow, Prefect).
Proficiency in a backend programming language like Python and solid SQL skills for querying and database design.
Familiarity with cloud platforms (AWS, GCP, or Azure) and their data services.
Process
This is what you can expect when we like your application:
30 minute recruiter call with Rachelle (Talent Lead)
30-minute call with Karthik (CTO)
Take-home coding challenge
60-minute review of your coding challenge with Karthik (virtual)
Onsite interview at our NYC office (or virtual for remote), including technical and behavioral/cultural components
Target Compensation
$200,000 – $220,000 + performance bonus + equity
Why Join Arlo:
High ownership: You’ll get real responsibility from day one—our high-trust team empowers you to run with big problems and shape core parts of the company.
Join an important mission: Your work directly influences how people access care and improves lives at scale.
Growth & expansion: We’re moving fast, and as we grow, your scope will grow with us—new challenges, bigger opportunities, and rapid career velocity.
Apply AI to a problem that matters: Instead of optimizing ads or cutting labor costs, you’ll use AI to fundamentally reimagine how people get healthcare.
High pace, high collaboration: We operate with velocity, first-principles thinking, and a team that works closely, openly, and with ambition.
Exact compensation inclusive of salary and any bonuses is determined based on a number of factors including experience and skill level, location, and qualifications which are assessed during the interview process.
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