We need someone to own quality at Eisen. The whole thing, not a piece of it. We’re processing billions of financial records for major banks, scaling fast, and shipping often. Quality can’t be something everyone sort of thinks about. It needs a person whose whole job is making sure what we ship actually works, and building the systems that make that repeatable.
This is one of those roles where you touch everything. You’ll work across the engineering team, sit in on architecture decisions, and have real say over what’s ready to go out the door. If quality is the thing you care most about in software, this is a good place to do that work.
About Eisen
Eisen is the first account offboarding platform for financial institutions. We handle escheatment, disbursement, and customer outreach for banks and fintechs, helping them close the loop on inactive accounts and get people back to their money.
We process billions of records daily. SSNs, account numbers, financial data. If we get something wrong, a bank’s customers are affected and regulators notice.
The Situation
Our peak ingestion hits about 2,500 records per second across MongoDB, Kafka, Bull, Redis, and Snowflake. We need to scale that 10x. We’re SOC 2 compliant, onboarding bigger financial institution customers, and adding new products to the platform constantly.
We’re building fast with Claude Code and shipping a lot of PRs. The deployment pipeline is feeling it. Increasing velocity shouldn’t mean decreasing quality, but someone needs to make sure that’s actually true. Right now, nobody is thinking about this full-time.
What You’ll Do
Test Infrastructure
Design and maintain automated tests across unit, integration, and E2E layers
Own CI/CD quality gates in GitHub Actions. If a pipeline is slow or unreliable, that’s your problem to fix
Build regression suites that catch real issues early in the development cycle
Set up performance and load testing. We need to know what breaks at 100M+ accounts before our customers find out
Figure out test data management so tests are reproducible across environments
Use AI tools (Claude, Cursor, Copilot) where they help. We’re not dogmatic about how you get there
Data Integrity and Compliance
Design testing around PII handling, encryption, and audit trails
Build quality gates that maintain SOC 2 compliance as we scale
Make it hard to ship a data integrity bug. Prevention over detection
Validate financial data transformations at every stage of the pipeline
Release Confidence
Define release certification so deploys feel safe, not nerve-wracking
