Fullstack Engineer, Ads — Remote-Eligible Growth Engine

Whatnot; New York (NY); Hybrid; USD 207,000 - 230,000; Full time

Benefits offered by this job

Health Insurance options

Work From Home Support

Home office setup allowance

Monthly internet allowance

Parental Leave

Retirement; 401k employer match (US)

Dogfood budget

Job summary

Whatnot, the leading live shopping platform in North America and Europe, is hiring a Fullstack Engineer to join our ads stack. You will own end-to-end features across backend and frontend, work with React, GraphQL, Python, and PostgreSQL, and ship rapidly while mentoring others.

This role is hybrid with options to work from home and requires proximity to our New York hub. Join a fast-growing team building impactful tools for sellers and buyers, collaborating across Discovery, Data, ML, and

Qualifications

• University degree or equivalent experience in CS or related field.
• Experience across the full technology stack (front-end to back-end).
• Strong React/GraphQL/Next.js frontend and Python/PostgreSQL backend experience.

Responsibilities

• Own end-to-end features across the ads stack.
• Collaborate with Discovery, Data Platform, ML, Payments teams.
• Mentor teammates and ship features quickly with quality.

Skills

Full-stack proficiency

Mentoring

Ownership

Autonomy

Product instincts

Problem solving

Fast shipping

Cross-functional collaboration

Education

Bachelor's degree in Computer Science or related field or equivalent experience

Tools

React

GraphQL

Next.js

Python

PostgreSQL

Job description

Whatnot, the leading live shopping platform in North America and Europe, is hiring a Fullstack Engineer to join our ads stack. You will own end-to-end features across backend and frontend, work with React, GraphQL, Python, and PostgreSQL, and ship rapidly while mentoring others.

This role is hybrid with options to work from home and requires proximity to our New York hub. Join a fast-growing team building impactful tools for sellers and buyers, collaborating across Discovery, Data, ML, and