Scale Engineer

Senior Software Engineer

Software EngineerL6Hard

The Senior Software Engineer (L6) interview process at Affirm is designed to assess a candidate's technical expertise, problem-solving abilities, system design skills, and cultural fit within the company. This role requires a strong understanding of software development principles, experience with large-scale systems, and the ability to mentor junior engineers.

Rounds·4

Timeline·~14d

Experience·5 - 10 yrs

Comp band·US$170000 - US$220000

Interview time·195 min

Evaluation

What they measure.

  • Technical proficiency in relevant programming languages and frameworks.
  • Ability to design scalable, reliable, and maintainable software systems.
  • Strong problem-solving and analytical skills.
  • Effective communication and collaboration skills.
  • Leadership potential and ability to mentor others.
  • Alignment with Affirm's values and culture.

Preparation

How to prepare.

Tips

  1. Review core computer science concepts, including data structures, algorithms, and complexity analysis.
  2. Practice coding problems on platforms like LeetCode, HackerRank, or Coderbyte, focusing on medium to hard difficulty.
  3. Study system design principles and common architectural patterns (e.g., microservices, RESTful APIs, caching, load balancing).
  4. Prepare to discuss your past projects in detail, highlighting your contributions, technical challenges, and impact.
  5. Research Affirm's products, services, and company culture to understand their business and values.
  6. Practice behavioral questions using the STAR method (Situation, Task, Action, Result).
  7. Prepare thoughtful questions to ask the interviewers about the role, team, and company.

Study plan

Fig · Study plan — 04 phases

01 / 04
01

Phase 01 of 04

Data Structures and Algorithms

Weeks 1-2: Data Structures & Algorithms. Practice coding problems daily.

Weeks 1-2: Focus on Data Structures and Algorithms. Cover arrays, linked lists, trees, graphs, hash tables, heaps, sorting, searching, dynamic programming, and greedy algorithms. Practice implementing these structures and algorithms and analyzing their time and space complexity. Aim for 2-3 coding problems per day.

Questions

Commonly asked.

  • Describe a time you had to make a significant technical decision with incomplete information. How did you approach it, and what was the outcome?
  • Design a URL shortening service like bit.ly.
  • How would you optimize the performance of a slow-running database query?
  • Tell me about a project where you had to collaborate with non-technical stakeholders. How did you ensure effective communication?
  • What are the trade-offs between monolithic and microservices architectures?
  • How do you handle technical debt?
  • Explain the concept of eventual consistency.
  • Describe a challenging bug you encountered and how you debugged it.
  • How would you design a system to handle millions of concurrent users?
  • What are your thoughts on test-driven development (TDD)?

Locations

Regional differences.

Fig · Regions — 02 locations

01 / 02

Location

San Francisco, CA

Interview focus

Deep dive into distributed systems and microservices architecture.Emphasis on scalability, performance optimization, and reliability in high-throughput environments.Behavioral questions focusing on leadership, mentorship, and cross-functional collaboration.System design questions tailored to financial technology and payment processing.

Common questions

  • How would you design a system to handle real-time fraud detection for Affirm's transactions?
  • Describe a complex technical challenge you faced and how you overcame it, focusing on the impact of your solution.
  • Discuss your experience with distributed systems and how you've ensured scalability and reliability.
  • How do you approach code reviews to ensure code quality and knowledge sharing?
  • Tell me about a time you had to influence a technical decision within a team. What was your approach and the outcome?

Tips

  • Be prepared to discuss specific examples of large-scale systems you've worked on.
  • Highlight your experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes).
  • Showcase your ability to mentor and lead technical discussions.
  • Understand Affirm's business model and how technology supports it.

Rounds

Round-by-round.

Expand a step for evaluation criteria, sample questions, and prep notes.

Med

Technical Interview (Coding) · 45 min · Software Engineer

This round focuses on your fundamental coding skills. You will be asked to solve one or two coding problems, typically involving data structures and algorithms. The interviewer will assess your ability to write clean, efficient, and correct code, as well as your approach to problem-solving and your understanding of time and space complexity.

What they look for

Clean, well-structured, and efficient code.A systematic approach to problem-solving.Clear communication of thought process.Ability to identify and discuss trade-offs.

Evaluation

  • Coding proficiency
  • Problem-solving approach
  • Understanding of data structures and algorithms
  • Code clarity and efficiency

Sample questions

  • Given an array of integers, find the contiguous subarray with the largest sum.

    ArrayDynamic Programming

  • Implement a function to reverse a linked list.

    Linked ListPointers

  • Find the kth smallest element in a binary search tree.

    TreeBinary Search TreeRecursion

Prep for this round

  1. 01Practice coding problems on platforms like LeetCode, focusing on common data structures (arrays, linked lists, trees, graphs, hash maps) and algorithms (sorting, searching, dynamic programming).
  2. 02Be prepared to explain your solution and discuss its time and space complexity.
  3. 03Practice writing code on a whiteboard or in a shared editor without relying on IDE features like auto-completion.

Common rejection reasons

  • ×Inability to articulate thought process clearly.
  • ×Lack of depth in understanding fundamental computer science concepts.
  • ×Poor coding practices or inefficient solutions.
  • ×Failure to consider edge cases or constraints.

DSA

Coding questions at Affirm.

Frequently reported on Affirm loops

View all at Affirm

Other guides

More at Affirm.