Remote Staff Backend Engineer – Search & Discovery

Affirm; Boise (ID); On-site; USD 204,000 - 290,000; Full time

Benefits offered by this job

Health coverage for you and dependents

Flexible Spending Wallets

Time off and holidays

Employee stock purchase plan

Job summary

Affirm is recruiting for a senior backend-focused engineer to shape technical strategy across a remote-first team. You will drive scalable backend design using Python or Kotlin, leverage AWS, MySQL, Spark and Kubernetes, and contribute to consumer-facing experiences with React.

You will also work on search and recommendation capabilities, influencing architecture and execution with strong cross-functional collaboration.

Qualifications

• 8+ years designing, developing and launching backend systems at scale.
• Proficient in Python or Kotlin.
• Experience with AWS, MySQL, Spark and Kubernetes.
• Experience building consumer experiences with React.
• 2+ years in search or related recommendation engines.
• Able to define technical and execution plans for major features.
• Strong written and verbal communication across teams.
• Bachelor’s degree or equivalent practical experience.

Responsibilities

• Set technical strategy for the team on a year-long horizon.
• Collaborate across product, design and analytics for sustainability and trade-offs.
• Define and advocate technical solutions and operational playbooks.
• Own team operations, monitoring, and on-call readiness.
• Establish and promote code design standards across teams.
• Mentor and develop team members with feedback and guidance.

Skills

Python

Kotlin

Distributed systems

AWS

MySQL

Kubernetes

React

Search engines

Education

Bachelor's degree in related field

Job description

Affirm is recruiting for a senior backend-focused engineer to shape technical strategy across a remote-first team. You will drive scalable backend design using Python or Kotlin, leverage AWS, MySQL, Spark and Kubernetes, and contribute to consumer-facing experiences with React.

You will also work on search and recommendation capabilities, influencing architecture and execution with strong cross-functional collaboration.