Software Engineer (Borrower Lender) - Full Stack Interview Process at Blend

As a candidate for the Software Engineer (Borrower Lender) - Full Stack role at Blend, you’ll be expected to demonstrate your proficiency in both front-end and back-end technologies, as well as an understanding of the user needs and workflows specific to the mortgage lending industry. The interview process focuses on assessing your technical skills, problem-solving abilities, and how you can contribute to developing solutions that will improve both the borrower and loan officer experiences.

Interview Process

Application and Initial Screening

The process typically starts with an online application or referral. Once your resume is reviewed, you may be contacted for an initial phone screen with a recruiter. This call is usually focused on your background, experience, and understanding of the company’s mission. The recruiter will also discuss the job role in more detail and may ask basic technical questions to gauge your fit for the role.

Technical Screen (Phone/Video)

After the initial screening, you’ll usually have a technical interview with an engineer. This interview is a coding round where you’ll be asked to solve problems related to data structures, algorithms, and system design. The problems are typically tailored to the full-stack environment, so you may encounter questions that require knowledge in both front-end and back-end technologies.

Example Question:

• “How would you design a loan approval system where data needs to be processed in real-time?”
  This tests your system design and understanding of scalable applications.

Expect to code live on a platform like CoderPad or Google Docs. Your problem-solving approach and clarity of thought are critical.

On-site Interview / Final Round (or Virtual On-site)

The final round usually consists of multiple technical interviews and a behavioral interview. You may have interviews with multiple engineers and managers. These interviews assess:

Front-End Development

Proficiency in JavaScript, HTML, CSS, and modern frameworks like React or Angular. You’ll likely be asked to build a feature or solve a problem that involves UI/UX considerations.

Example Question:

• “Implement a responsive form where users can enter loan information, and the form updates dynamically based on the input.”

Back-End Development

Strong understanding of backend technologies such as Node.js, Golang, or TypeScript, and familiarity with databases like MongoDB or Postgres.

Example Question:

• “Design a system that handles high throughput and concurrency, such as an API for processing loan applications.”

System Design

Expect questions on architecture, scalability, and handling large-scale systems.

Example Question:

• “How would you scale a loan processing platform to handle millions of users applying simultaneously?”

Behavioral Interview

Here, you’ll be assessed on how you handle challenges, work in teams, and contribute to a product. Expect to be asked about past experiences, especially where you’ve worked in teams and handled complex projects.

Example Question:

• “Tell me about a time when you disagreed with a team member. How did you resolve the issue?”

Code Review and Collaboration

During the interview, you might also participate in a code review session where you’ll review a piece of code and suggest improvements. This tests your ability to work collaboratively and improve code quality.

Example Task:

• Review a piece of code for the loan application API and suggest optimizations.

Final Discussion

If you pass the technical rounds, you’ll have a final conversation with the hiring manager or a senior engineer to discuss the offer, team dynamics, and expectations for the role.

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Commonly Asked Interview Questions

Technical Questions

• How would you design a system to handle loan document management for both borrowers and loan officers?
• Explain the difference between SQL and NoSQL databases and give an example of when you’d use each.
• Write a function to find the shortest path between two nodes in a graph. Implement this using BFS or DFS.

System Design Questions

• Design a system that allows users to submit loan applications and track their status.
• How would you build a scalable notification system for loan status updates?

Front-End Questions

• Build a responsive form for submitting mortgage applications. What are the key considerations for accessibility?
• What are the differences between React and Angular? Which would you choose for a project and why?

Behavioral Questions

• Tell me about a time when you had to meet a tight deadline. How did you manage your time?
• Describe a challenging project you worked on. How did you approach solving the problem?

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Tips for Preparation

• Understand the Role: Blend focuses on simplifying the mortgage process. Ensure that you understand the Borrower Lender team’s mission and the tools Blend uses, such as APIs and cloud services.
• Brush Up on Full-Stack Technologies: Make sure you’re comfortable with both front-end (React, JavaScript) and back-end (Node.js, Golang) development. Also, review databases like Postgres and MongoDB.
• Prepare for Behavioral Questions: Blend values a collaborative and transparent environment, so practice situational and behavioral questions that highlight your teamwork and problem-solving skills.
• System Design: Practice designing scalable systems that handle complex workflows, as scalability is key to Blend’s products.

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Example of a System Design Question

Question:
How would you design a loan approval system for a large-scale platform like Blend, where speed and accuracy are critical?

Answer:
To design a scalable loan approval system, I would use a microservices architecture to separate different concerns like user authentication, loan application, credit scoring, and document management. Each service would be independently scalable.

• API Gateway: All requests would go through an API gateway to ensure security and load balancing.
• Data Storage: For storing application data, I would use a combination of relational databases like Postgres for structured data and NoSQL databases like MongoDB for storing unstructured data like scanned documents.
• Message Queues: To ensure asynchronous processing (e.g., processing background tasks like credit scoring), I would use message queues like Kafka or RabbitMQ.
• Microservices: Each service would be independently deployable and responsible for a single functionality (e.g., loan application, credit check). This would allow for better fault tolerance and easier scaling.
• Real-Time Notifications: For user updates, I would use a pub/sub system to notify users in real-time when their application status changes.