A Software Engineer at Shift Technology plays a pivotal role in shaping the future of insurance decision automation. The company leverages advanced artificial intelligence and machine learning to help global insurance providers detect fraud, automate claims processing, and optimize underwriting decisions. In this role, you are not just writing code; you are building the secure, high-throughput, and resilient infrastructure required to ingest, process, and analyze massive volumes of complex financial and personal data.

The impact of your work is immediate and highly visible. By developing clean, optimized, and scalable backend services and intuitive frontend interfaces, you directly enable insurance companies to detect sophisticated fraud networks in real time. The technical challenge is immense, requiring a deep understanding of distributed systems, complex data pipelines, and robust security paradigms to ensure the platform remains highly performant under heavy transactional loads.

To succeed as a Software Engineer here, you must thrive in an environment that values deep technical expertise, algorithmic precision, and architectural discipline. You will collaborate closely with data scientists, product managers, and fellow engineers to transform complex business logic into elegant, maintainable code. Whether optimizing SQL queries, refining machine learning deployment pipelines, or designing reusable frontend components, your contributions will directly drive the scaling of Shift Technology's core SaaS platform.

The questions you will encounter during the hiring process at Shift Technology are designed to evaluate both your academic computer science knowledge and your practical software design capabilities. While the exact questions will vary depending on your target team and seniority, they consistently follow clear patterns focused on logical reasoning, data manipulation, and clean code principles.

Algorithms & Data Structures

These questions assess your ability to write optimized code and analyze its performance under pressure.

• Explain the time and space complexity (Big O notation) of your proposed solution.
• How would you optimize a search algorithm to run in logarithmic time instead of linear time?

Preparing for an interview at Shift Technology requires a balanced approach. You must be ready to demonstrate both strong theoretical computer science fundamentals and practical, hands-on coding proficiency. The engineering team values candidates who can clearly articulate their thought process and justify their architectural choices.

Computer Science Fundamentals – You must have a strong grasp of data structures, algorithms, and complexity analysis. Expect to be evaluated on your ability to write clean code without relying on modern IDE helper tools.

System & Database Design – You need to understand how web services function, how databases are structured, and how to write efficient SQL queries. Be prepared to discuss indexing, transaction isolation levels, and concurrency models.

Communication & Collaboration – Interviewers look for engineers who can explain complex technical concepts simply. You should be prepared to discuss your past experiences, team dynamics, and how you approach problem-solving in a collaborative environment.

The recruitment process at Shift Technology is rigorous, multi-staged, and highly technical. It typically spans three to four weeks and is designed to thoroughly evaluate your technical capability, logical reasoning, and cultural alignment. Candidates should expect a structured sequence of conversations and coding exercises that assess both frontend and backend competencies where applicable.

The journey begins with an initial HR screening, followed by a technical assessment or phone screen with an engineer. If you pass these initial stages, you will move into intensive technical rounds focusing on live coding, system design, and clean code principles. The process culminates in interviews with engineering managers, directors, or executive leadership (such as the CTO) to evaluate your overall fit for the team.

The timeline above outlines the typical progression from your initial application to the final hiring decision. You should use this visual roadmap to pace your preparation, ensuring you dedicate sufficient time to coding practice before the technical rounds. While some stages may run concurrently depending on team availability, the overall structure remains highly consistent across global offices.

To excel in the Shift Technology interview process, you must understand the specific competencies being evaluated at each stage. The engineering team looks for precise indicators of technical maturity, code quality, and problem-solving structuredness.

Algorithmic Coding & Logic

This area evaluates your core programming capabilities under timed conditions. You will face live coding challenges that require you to write functional, bug-free code to solve algorithmic problems.

Be ready to go over:

• Time and Space Complexity – Analyzing your code using Big O notation and identifying bottlenecks.
• Data Structure Selection – Choosing the right structures (e.g., hash maps, trees, queues) to optimize performance.
• Edge Case Handling – Identifying and coding defenses against null inputs, boundary limits, and unexpected data formats.
• Advanced concepts (less common) – Dynamic programming, graph traversal algorithms, and custom memory management.

Example scenarios:

• Implementing an algorithm to find the shortest path in a network of connected financial transactions.
• Writing a custom parser to validate and structure incoming raw insurance event logs.

Object-Oriented Design & Clean Code

Shift Technology places a premium on code maintainability and architectural discipline. You will be asked questions that test your ability to design scalable, readable, and testable software systems.

Be ready to go over:

• SOLID Principles – Demonstrating a deep, practical understanding of how to apply these principles to real-world code.
• Design Patterns – Knowing when to implement creational, structural, and behavioral patterns.
• Asynchronous Programming – Understanding how async/await patterns function and how they impact resource utilization.
• Advanced concepts (less common) – Domain-Driven Design (DDD), microservices communication patterns, and event sourcing.

Example scenarios:

• Refactoring a tightly coupled, monolithic class into a modular, highly testable set of services.
• Designing an extensible notification system that supports multiple delivery channels (email, SMS, webhook) using OOP design patterns.

Database & Data Layer Proficiency

Because the company deals with massive datasets, your ability to interact efficiently with databases is critical. Expect direct questions about SQL, data modeling, and data retrieval efficiency.

Be ready to go over:

• SQL Query Optimization – Writing and refining complex queries involving multiple joins, subqueries, and aggregations.
• Database Indexing – Explaining how B-trees work and how to design indexes that speed up read operations without crippling writes.
• Concurrency & Transactions – Understanding ACID properties, lock types, and how to handle concurrent data updates.

Example scenarios:

• Explaining how you would diagnose and fix a performance bottleneck in a production database experiencing high write latency.
• Designing a relational database schema to represent a complex, multi-party insurance claim workflow.