HarveyAI Software Engineer interview questions & guide 2026

The following questions are representative of the patterns observed in our interview process. While specific inquiries may shift based on the project focus of the team you are interviewing with, you should anticipate a strong emphasis on your ability to translate abstract requirements into concrete, performant code.

Data Structures and Algorithm Design

This category evaluates your ability to select optimal storage mechanisms and handle complex logic, such as dependency management.

• Implement a setCell and getCell functionality using optimal data structures.
• Extend your cell storage to handle formulas (e.g., '=B1+5') and manage updates for dependent cells.

Preparation for HarveyAI should focus on bridging the gap between theoretical computer science and practical, system-level implementation. Do not simply memorize algorithms; instead, focus on explaining the "why" behind your technical choices.

Technical Competency – You must demonstrate mastery over fundamental data structures and algorithmic complexity. Interviewers look for your ability to optimize for time and space, especially when dealing with recursive structures or large datasets.

System Design Thinking – Success here requires an ability to think beyond a single service. You will be evaluated on your understanding of distributed systems, database choices, and the security implications of handling sensitive data.

Values Alignment – Our culture is a core component of the interview. You should be prepared to articulate your professional journey and decision-making process in a way that resonates with our specific organizational values.

Communication and Clarity – Even if your code is correct, your process matters. You are expected to communicate your assumptions, discuss trade-offs openly, and respond constructively to follow-up questions from your interviewer.

The interview process at HarveyAI is designed to be rigorous, collaborative, and reflective of the actual challenges our engineers solve daily. You will typically move through a series of stages that test your coding proficiency, your architectural design skills, and your cultural fit. The pace is generally fast, and you should expect interviewers to push you on the details of your solutions to see how you handle pressure and feedback.

The timeline above illustrates the progression from initial technical assessment through final behavioral and design rounds. You should use this to pace your preparation, ensuring you have enough time to review both foundational coding concepts and broader system architecture topics. Note that the process is highly iterative; expect follow-up questions that challenge your initial designs.

Algorithmic Problem Solving

We test your ability to solve complex, non-trivial problems under time constraints. Focus on efficiency and edge-case handling.

• Dependency Graphs: Understanding how to represent and traverse directed graphs.
• Recursive Logic: Implementing DFS and handling cycles or exceptions.
• Complexity Analysis: Being able to justify your time and space complexity choices in real-time.

System Architecture

We assess your ability to build systems that are not only functional but also maintainable and scalable.

• Storage Strategy: Understanding when to use a metadata store versus a blob store.
• Access Control: Designing systems that respect organization-level permissions.
• Scalability: Addressing how to handle large files and high-concurrency requests.

As a Software Engineer, your daily life will involve deep work on the core engine that powers HarveyAI. You will spend a significant portion of your time designing and implementing new features that involve complex data manipulation, such as the spreadsheet-like logic or document management systems described in our interview scenarios.

You will collaborate closely with product managers and other engineers to translate ambiguous requirements into technical specifications. This includes performing code reviews, contributing to the overall system design, and ensuring that our infrastructure remains performant as we scale. You are expected to be an active participant in architectural discussions, often weighing in on the trade-offs between speed of delivery and long-term technical debt.

A strong candidate for this role possesses a deep technical foundation combined with the ability to operate in an environment where AI technology is rapidly shifting.

• Must-have skills: Proficiency in at least one major programming language, strong understanding of data structures (graphs, trees, hash maps), and experience with system design principles.
• Nice-to-have skills: Experience with cloud-based storage solutions, familiarity with ACL implementation, and prior work in AI-integrated product development.
• Soft skills: Clear communication, a proactive approach to problem-solving, and the ability to articulate technical trade-offs to non-technical stakeholders.

Q: How difficult are the coding rounds? A: The coding rounds are of medium difficulty but require a high degree of precision. You should be comfortable implementing data structures from scratch and explaining the time complexity of your solutions.

Q: Is there feedback provided if I am not selected? A: While we strive to provide a positive candidate experience, we do not always provide detailed feedback for every applicant. Focus on self-reflection after each round to identify your own areas for improvement.

Q: How much should I focus on AI/ML knowledge? A: While this is an AI company, the Software Engineer role primarily focuses on building the robust infrastructure that enables AI. A solid foundation in general software engineering is more critical than deep ML research experience.

Q: How long is the typical interview process? A: The process typically spans several weeks, including a mix of remote coding sessions and an onsite or virtual final round.

• Think Aloud: Your interviewer is more interested in your thought process than just the final code. Explain your assumptions early and often.
• Prioritize Edge Cases: When solving problems, proactively identify potential failure modes, such as circular dependencies or empty inputs, before the interviewer points them out.
• Clarify Requirements: If a question seems ambiguous, ask clarifying questions before jumping into the implementation. This is a sign of a senior-level approach.
• Study System Design: Don't just focus on LeetCode-style problems. Review how to design large-scale systems, focusing on components like databases, APIs, and access control.

The Software Engineer position at HarveyAI is an opportunity to build the future of professional services through advanced software engineering. By mastering the core competencies of data structures, system architecture, and clear, values-driven communication, you will position yourself as a top-tier candidate.

Your preparation should be structured and iterative. Use the themes identified in this guide to build your own study plan, focusing on your weakest areas first. We encourage you to continue exploring insights and refining your approach to technical interviews. You have the potential to make a significant impact here—prepare with intent, and approach each round as an opportunity to demonstrate your engineering excellence.

The provided salary data reflects typical compensation ranges for this role, including base salary and potential equity components. Candidates should interpret these figures as market-standard benchmarks that may vary based on your specific level of experience, geographic location, and the unique requirements of the team you join.