Senior Mobile Engineer
Forage · payments
senior
Salary Range (USD)
$185k - $200k
Location
NYC, USA
Visa Support
Not mentioned
Funding Stage
YC-backed (W21)
Job Responsibilities
- • own the frontend of the mobile app
- • work closely with a small product and design team
- • ship features that put real dollars back in low-income families' pockets
Required Skills
3+ years of mobile engineering experiencedeep React Native experience
Engineering Culture & Tech Stack
React Native
lead technical initiatives
mentor engineers
drive complex projects from design through execution
Raw Post
Show original text
Forage | Senior Mobile Engineer (React Native) | Hybrid NYC (2-3 days in office) | Full-time | $185,000 - $200,000 per year base | joinforage.com
Forage is a payments company building the infrastructure for SNAP EBT online. About 1 in 8 Americans (over 40 million people) use SNAP to buy groceries, and we process the EBT payments that let them shop on Uber Eats, DoorDash, and at major grocery chains. We're now building our first consumer product: a mobile app that surfaces cash rewards at partner merchants so EBT shoppers can stretch their benefits further and put more food on the table.
We're hiring a Senior Mobile Engineer to own the frontend of this app. You'll oversee significant parts of the codebase, work closely with a small product and design team, and ship features that put real dollars back in low-income families' pockets.
A good fit:
- You have 3+ years of mobile engineering experience building end to end user solutions
- You have deep React Native experience, ideally having built an app from scratch or meaningfully contributed to a production app
- A track record of leading technical initiatives, mentoring engineers, and driving complex projects from design through execution
YC-backed (W21), well funded, competitive comp and equity.
Apply: https://jobs.gem.com/-joinforage/am9icG9zdDoQzZQuSvDKMNwsFFJ...
Please mention HN in your application.
AI Risk Insights
No major risk signals detected.
Recent News
No recent updates
Data Source
Content parsed by LLM from Hacker News raw data. Confidence:HIGH