Founding Engineer - Backend & Data Platform
Greenline
Software Engineering
Posted on Mar 18, 2026
⛏️
Founding Engineer - Backend & Data Platform
Job Posted
July 31, 2025 4:59 PM
Location
SF
Austin
Remote
NYC
Team
Engineering
About Greenline
At Greenline, we're dedicated to unlocking mortgage lending for self-employed and non-traditional borrowers.
We’re a small and nimble team that values brains, empathy, and hustle. Our team operates remotely, and we’ll give preference to candidates in the SF Bay Area, Austin, and NYC.
Greenline’s engineers are involved throughout the product lifecycle, from idea generation and design to prototyping and production delivery. You will partner closely with engineering and non-technical teammates to understand our customers' problems and ship solutions accordingly. You’ll have high agency and a strong bias toward action.
Job Description
Greenline’s founding backend and data platform engineer will transform how lenders and related parties use our insights.
This is a senior- /staff-level individual contributor role with architectural influence. You will design resilient data pipelines and collaborate with product and compliance stakeholders to ensure correctness, auditability, and extensibility.
This is not a research role. Rather, this is an underdeveloped area at Greenline for you to shape and own, which will include:
Core Infrastructure - build the foundational platform for Greenline products and services to operate at scale. We drive reliability, availability, efficiency, and scalability of these systems. You’ll collaborate on a mix of platform, infrastructure, and product problems to ensure Greenline thrives in a heavily regulated industry.
Data Integrations & Platform – ingestion, normalization, and analysis of third-party financial data from external data sources, including:
Banking and asset data (Plaid, Finicity, MX)
Tax and income data (IRS transcripts, W-2/ 1099 sources)
Accounting platforms (QuickBooks, Xero, similar systems)
You’ll own the data-serving infrastructure, including:
Authentication and authorization
Webhooks, de-duplication, and backfill strategies
Rate limiting, retries, idempotency, and error classification
Design integration layers that isolate vendor-specific behavior and support future provider swaps.
Data normalization & canonical modeling
Analytics & Applied ML Enablement – develop feature pipelines, validation, and productionizing signals.
Implement feature extraction pipelines suitable for downstream analytics and ML usage
Develop in-house and apply off-the-shelf ML models and services (e.g., BERT, classification, clustering, anomaly detection)
Collaborate with product and business stakeholders to translate model outputs into actionable insights
Responsibilities
Collaborate with cross-functional teams to develop and implement machine learning models, algorithms, and ledger-based technologies.
Build performant and scalable systems for storage, auth, or asset serving to enable other product teams to build robust applications.
Design relational database schemas in Postgres and manage SQL migrations.
Maintain and evolve testing pipelines, Docker builds, and rollout processes for backend services, leveraging blue/green or canary deployments as needed.
Must-Have Skills
Experience designing and operating:
Data ingestion pipelines
Event-driven or batch processing systems
APIs that support downstream analytics
Deep understanding of relational databases and data modeling (Postgres strongly preferred)
Demonstrated ability to reason about:
Data correctness and reconciliation
Auditability and traceability
Long-lived data contracts
Solid understanding of ML fundamentals, including:
Supervised vs. unsupervised learning
Feature engineering concepts
Model evaluation metrics (precision/recall, ROC, confidence intervals)
Overfitting, bias, and data leakage
Practical experience:
Consuming ML models via APIs or SDKs
Using statistical techniques to validate data outputs
Debugging ML-driven systems without being the model author
Comfort working with datasets using SQL, Python notebooks, or similar tools.
Nice-to-Have Skills
Experience with GraphQL.
Proficiency in TypeScript.
Experience with monorepo tooling, ideally using yarn, npm, or pnpm workspaces.
Experience with and interest in React or NextJS.
Tech Stack
Postgres DB accessible through a GraphQL API built with Hasura
NextJS web application deployed to Vercel
yarn workspace monorepo utilizing TypeScript
Playwright + Jest testing with ~80% test coverage
Pay & Benefits
The annual U.S. base salary range for this role is $175,000 - $225,000 with aggressive equity.
Additional benefits for this role include: medical, dental, and vision benefits; open and flexible time off; and wellness stipends.
Final offer amounts are determined by multiple factors including candidate experience and expertise. Compensation may vary from the amounts listed.
To Apply
Excited about this opportunity? Send us a note: hello@greenline.ai
Don’t meet every single requirement? Studies have shown that women and people of color are less likely to apply for jobs unless they meet every qualification. If your experience doesn’t align perfectly with every qualification above, we encourage you to apply. You may be the perfect candidate!