Preparation is the key to demonstrating your full potential during the interview loop. Your goal is to show not just that you can write code, but that you can design resilient systems and thrive in an ambiguous, fast-moving environment.

Technical Excellence – You must demonstrate a deep command of computer science fundamentals, data structures, and algorithms. Interviewers will evaluate your ability to write clean, optimized, and bug-free code under pressure, as well as your fluency in the primary languages used in your specific domain (e.g., C++, Python, or TypeScript).

System Design and Architecture – This assesses your ability to scale systems and make intelligent architectural trade-offs. You will be evaluated on how well you can design complex, distributed systems or domain-specific architectures, balancing constraints like latency, throughput, reliability, and security.

Domain Expertise – Because Software Engineer roles at & General Intuition span diverse areas like Perception, Operating Systems, UI Toolkits, and Cloud Infrastructure, you will be tested on the specific frameworks, protocols, and paradigms relevant to your track. Strong candidates seamlessly connect theoretical knowledge to practical, domain-specific implementations.

Problem-Solving and Ambiguity – Interviewers want to see how you approach vaguely defined problems. You are evaluated on your ability to ask the right clarifying questions, break down complex challenges into manageable components, and iterate on your solutions based on new constraints.

Collaboration and Culture – We look for engineers who elevate their teams. You will be assessed on your communication skills, your approach to cross-functional collaboration, how you handle disagreements, and your ability to mentor others and drive projects to completion.

The interview process for a Software Engineer at & General Intuition is rigorous, structured, and highly calibrated to assess both your technical depth and your problem-solving methodology. Your journey typically begins with a recruiter screen to align on your background, track preference (e.g., ML, Frontend, Infra), and location expectations. This is followed by one or two technical phone screens, which are heavily focused on data structures, algorithms, and your ability to write executable code in a shared editor.

If you advance, you will participate in an onsite interview loop, which is currently conducted virtually. The onsite loop generally consists of four to five rounds. You can expect a mix of advanced coding rounds, a comprehensive system design or architecture interview, a domain-specific deep dive tailored to your target team, and a behavioral round focused on your past experiences and cultural alignment.

Our interviewing philosophy is deeply collaborative. Interviewers are not trying to trick you; they want to see how you work through problems as a teammate. Expect them to probe your assumptions, ask follow-up questions, and introduce new constraints mid-interview to see how you adapt.

The visual timeline above outlines the standard progression from initial recruiter contact through the final onsite rounds. Use this to pace your preparation, ensuring you peak in your coding fluency early on, while reserving time to deeply review system design and behavioral narratives before the onsite stage. Note that the exact sequence and domain-specific rounds may vary slightly depending on whether you are interviewing for a specialized track like Perception ML or Frontend Mission Control.

Data Structures and Algorithms

This area forms the foundation of our technical evaluation. We need to ensure you can write highly efficient, production-ready code. Interviewers will look for your ability to choose the optimal data structures, understand time and space complexity, and translate your logic into clean, compilable code. Strong performance means arriving at an optimal solution while proactively communicating your thought process.

Be ready to go over:

• Graphs and Trees – Traversals (BFS/DFS), shortest path algorithms, and tree balancing.
• Dynamic Programming – Identifying overlapping subproblems and optimizing recursive solutions.
• Concurrency and Multithreading – Thread safety, locks, and managing shared state (especially critical for OS and Infra roles).
• Advanced concepts (less common) – Tries for autocomplete features, topological sorting for build systems, and advanced heap manipulations.

Example questions or scenarios:

• "Design an algorithm to parse and process massive streams of telemetry data in real-time."
• "Implement a thread-safe rate limiter for an API endpoint."
• "Write a function to find the shortest path for a robotic agent navigating a grid with dynamic obstacles."

System Design and Architecture

System design interviews test your ability to look at the big picture. We evaluate how you design systems that are scalable, highly available, and fault-tolerant. Strong candidates drive the conversation, define clear APIs, sketch out the major components, and openly discuss the trade-offs of their architectural choices (e.g., consistency vs. availability, SQL vs. NoSQL).

Be ready to go over:

• Distributed Systems – Microservices architecture, load balancing, and partitioning strategies.
• Data Storage and Caching – Database selection, replication, caching layers (Redis/Memcached), and data modeling.
• Asynchronous Processing – Message queues (Kafka, RabbitMQ), event-driven architectures, and background job processing.
• Advanced concepts (less common) – Consensus algorithms (Paxos/Raft), edge computing architectures, and real-time video streaming protocols.

Example questions or scenarios:

• "Design a mission control dashboard that aggregates and displays real-time telemetry from thousands of remote devices."
• "Architect a scalable cloud infrastructure to process and store petabytes of machine learning training data."
• "Design a distributed job scheduler for our internal developer infrastructure."

Domain-Specific Deep Dives

Because & General Intuition hires for specialized tracks—ranging from Perception Engineering and Prediction ML to UI Toolkits and Operating Systems—you will face a round dedicated to your specific area of expertise. We evaluate your depth of knowledge in the tools, frameworks, and low-level mechanics of your domain.

Be ready to go over:

• Frontend / UI Toolkit – Browser rendering optimization, state management (React/Redux), and component architecture.
• Machine Learning / Perception – Model deployment, data pipelines, sensor fusion concepts, and performance tuning for inference.
• Operating Systems / C++ – Memory management, kernel-level debugging, inter-process communication, and low-latency optimizations.
• Advanced concepts (less common) – Hardware-in-the-loop testing, custom rendering engines, or writing custom network protocols.

Example questions or scenarios:

• "Explain how you would optimize a React-based customer portal that is rendering thousands of dynamic data points."
• "Walk me through how you would deploy a behavior prediction model to a resource-constrained edge device."
• "Debug a memory leak in a multi-threaded C++ application used for systems engineering."

Behavioral and Cross-Functional Collaboration

Building complex autonomous and AI-driven systems requires tight coordination across diverse teams. This round evaluates your emotional intelligence, leadership, and resilience. Strong performance involves using the STAR method (Situation, Task, Action, Result) to provide concise, reflective answers that highlight your ability to handle conflict, mentor peers, and navigate shifting priorities.

Be ready to go over:

• Navigating Ambiguity – How you operate when requirements are unclear or rapidly changing.
• Conflict Resolution – How you handle technical disagreements with peers or product managers.
• Ownership and Delivery – Examples of times you took end-to-end responsibility for a critical feature or system failure.
• Advanced concepts (less common) – Leading cross-team architectural migrations or managing vendor relationships for IT operations.

Example questions or scenarios:

• "Tell me about a time you had to pivot your technical approach halfway through a project due to changing product requirements."
• "Describe a situation where you strongly disagreed with a senior engineer's architectural proposal. How did you resolve it?"
• "Walk me through the most complex bug you've ever tracked down in a production environment."

As a Software Engineer at & General Intuition, your daily responsibilities will heavily depend on your specific team, but the core expectation is taking ownership of complex technical challenges. You will design, develop, and maintain software that operates at the intersection of hardware, AI, and user experience. This involves writing high-quality, heavily tested code, conducting rigorous code reviews, and ensuring your systems meet strict performance and reliability SLAs.

You will collaborate constantly. Whether you are a Cloud Infrastructure Engineer working with ML researchers to optimize training pipelines, or a Frontend Engineer building Mission Control tools for operations teams, cross-functional communication is a daily requirement. You will participate in architecture design reviews, write comprehensive technical design documents (TDDs), and help define the technical roadmap for your team.

Furthermore, you will be responsible for operational excellence. This means setting up monitoring and alerting, participating in on-call rotations, and driving blameless post-mortems when incidents occur. You will continuously look for ways to improve developer velocity, whether by building better internal AI tooling, optimizing build times, or refining the CI/CD pipelines.

To thrive as a Software Engineer at & General Intuition, you must possess a strong foundation in computer science and a proven track record of delivering production-grade software. The expectations scale with the seniority of the role, but core technical competence is non-negotiable.

• Must-have technical skills – Proficiency in at least one core language (C++, Python, Java, Go, or TypeScript/React depending on the role). Strong grasp of data structures, algorithms, and system design principles. Experience with modern software development practices (version control, CI/CD, automated testing).
• Must-have experience – A Bachelor’s degree in Computer Science, Computer Engineering, or a related field (or equivalent practical experience). Experience building and scaling distributed systems or complex user interfaces.
• Must-have soft skills – Exceptional problem-solving abilities, clear technical communication, and a collaborative mindset. The ability to articulate complex technical trade-offs to non-technical stakeholders.
• Nice-to-have skills – Advanced degrees (Master's or Ph.D.) for ML/Perception roles. Experience with robotics, autonomous systems, low-latency computing, or specialized cloud environments (AWS/GCP). Familiarity with hardware/software integration.