Preparing for Moveworks.Ai requires a structured approach that balances algorithmic mastery with practical systems thinking. The hiring bar is notoriously rigorous, and the team evaluates candidates across several core dimensions.

Technical Rigor & Edge Cases – Moveworks.Ai interviewers place a heavy emphasis on your ability to write production-grade code. When coding, you must not only find the optimal algorithmic complexity but also proactively identify and handle complex edge cases. Your code is expected to be clean, modular, and syntactically correct.

System Design & Scalability – You must demonstrate a deep understanding of distributed systems. This means going beyond high-level block diagrams to explain the "why" behind your architectural choices. Be ready to discuss database selection, data consistency models, API design, and failure recovery in detail.

Problem-Solving under Ambiguity – Many technical prompts at Moveworks.Ai are intentionally open-ended. Interviewers want to see how you gather requirements, ask clarifying questions, and break down a massive problem into manageable, structured components before writing any code or drawing any diagrams.

Collaboration & Cultural Alignment – The company values a highly collaborative, ego-free working style. Throughout your conversations, demonstrate humility, receptiveness to feedback, and a strong sense of ownership. Showing that you are easy to work with and receptive to hints is just as important as solving the technical problem.

The interview process at Moveworks.Ai is thorough, comprehensive, and designed to gather deep signal on your technical capabilities and cultural fit. Candidates should prepare for a multi-stage journey that typically spans three to four weeks from the initial application to the final decision.

The journey begins with a standard recruiter screen to align on your background and expectations. This is followed by a technical screening phase, which usually consists of one or two coding interviews focusing on data structures and algorithms. Once you clear the screening phase, you will move to a highly intensive virtual onsite loop. This loop is demanding and can take between six to eight hours, often spread across one or two days, depending on scheduling.

The onsite loop typically includes two coding rounds, two system design rounds (covering both high-level and low-level design), a presentation or product demo session, and conversations with the hiring manager and senior leadership. While some candidates have described the process as lengthy and demanding, those who succeed emphasize that the team is looking for exceptional problem-solving depth and structured thinking.

The visual timeline above outlines the typical progression of the Moveworks.Ai interview pipeline. Candidates should use this timeline to pace their preparation, ensuring they are fully prepared for the algorithmic screens before shifting their focus to the intensive system design and presentation rounds of the onsite loop.

To excel in the Moveworks.Ai technical rounds, you must understand the specific competencies evaluated in each session.

Coding and Algorithmic Problem Solving

The coding rounds at Moveworks.Ai focus heavily on your ability to translate complex logic into clean, working code. These rounds are typically conducted via collaborative coding platforms. Interviewers expect you to talk through your thought process out loud, discuss time and space complexity upfront, and write bug-free code.

Be ready to go over:

• String Manipulation & Parsing – Implementing custom parsers, handling nested expressions, and managing complex string transformations.
• Recursion & Backtracking – Solving search-space and optimization problems using recursive strategies, and optimizing them with memoization.
• Data Structure Optimization – Knowing when and how to leverage hash maps, sets, queues, and heaps to achieve optimal runtimes.
• Advanced concepts (less common) – Multi-dimensional dynamic programming, trie implementations for prefix searching, and complex graph traversal algorithms.

Example scenarios:

• Implementing an expression evaluator that respects custom operator precedence and parenthesis nesting.
• Designing an algorithm to find all valid combinations of dictionary words within a continuous string of characters.

System Design (HLD and LLD)

System design at Moveworks.Ai is split into High-Level Design (HLD) and Low-Level Design (LLD). HLD sessions focus on overall architecture, scalability, and data flow. LLD sessions focus on class structures, API contracts, design patterns, and how you would organize code within a microservice.

Be ready to go over:

• Distributed Scheduler Design – Designing systems that can trigger tasks reliably at scale, handling worker failures, and ensuring at-least-once or exactly-once execution.
• API and Schema Design – Defining clear REST or gRPC endpoints, database schemas, and data serialization formats.
• Data Consistency & Caching – Managing cache invalidation, database replication, and choosing between SQL and NoSQL databases based on system requirements.
• Advanced concepts (less common) – Rate limiting algorithms, event-sourcing architectures, and designing for partition tolerance in distributed environments.

Example scenarios:

• Designing a system that polls external APIs (such as ticket updates from an IT service desk) and processes those updates in real time.
• Architecting a rate-limiting service that protects downstream microservices from traffic spikes.

Product Demo & Presentation Round

A unique element of the Moveworks.Ai onsite loop is the presentation or product demo round. This round evaluates your ability to communicate technical value, explain complex architectures to cross-functional stakeholders, and demonstrate practical engineering empathy.

Be ready to go over:

• Technical Presentation – Presenting a project you have built in the past, explaining the architecture, the challenges faced, and the business impact.
• Integration Scoping – Discussing how to integrate third-party systems, mapping data fields, and handling authentication and sync schedules.
• Value Demonstration – Showing how your engineering decisions directly translate into user experience and product reliability.