What is a Software Engineer at & General Intuition?

As a Software Engineer at & General Intuition, you are at the forefront of building the critical systems that power our advanced technologies. Whether you are developing low-latency operating systems, designing scalable cloud infrastructure, training prediction and behavior machine learning models, or crafting intuitive mission control interfaces, your work directly translates into the safety, reliability, and performance of our core products.

This role requires navigating immense technical complexity. You will be tackling problems that do not have standard industry solutions, requiring you to innovate across the entire software stack. The impact of your position is profound; the code you write will bridge the gap between complex AI tooling, hardware systems, and end-user experiences, driving the operational success of our deployments in real-world environments.

Expect a highly collaborative, fast-paced environment where you will work alongside researchers, hardware engineers, and product leaders. At & General Intuition, we value engineers who are not only exceptional coders but also strategic thinkers capable of architecting robust systems from the ground up. You will be challenged to push the boundaries of what is possible in robotics, AI tooling, and distributed systems.

Getting Ready for Your Interviews

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.

Interview Process Overview

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.

Deep Dive into Evaluation Areas

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."

Key Responsibilities

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.

Role Requirements & Qualifications

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.

Common Interview Questions

The following questions are representative of the types of challenges you will face during your interviews. They are drawn from patterns observed in our hiring process and are meant to help you understand the depth and style of our evaluation, rather than serve as a memorization list.

Coding and Algorithms

These questions test your ability to translate logic into efficient code. Interviewers will look for optimal time and space complexity and clean implementation.

• Implement an LRU (Least Recently Used) cache with O(1) time complexity for get and put operations.
• Write an algorithm to serialize and deserialize a binary tree.
• Given a stream of incoming coordinates from a perception sensor, design a sliding window algorithm to calculate the moving average.
• Implement a thread-safe bounded blocking queue.
• Find the longest palindromic substring in a given string.

System Design and Architecture

These questions evaluate your ability to design scalable, fault-tolerant systems. Focus on the architecture, data flow, and trade-offs.

• Design a real-time telemetry ingestion pipeline capable of handling millions of events per second from remote hardware.
• Architect a distributed key-value store. How would you handle replication and consistency?
• Design the backend infrastructure for a developer portal that orchestrates complex CI/CD builds.
• How would you design an alerting system for our Mission Control operations team?
• Design a scalable rate-limiting service for our external API.

Domain-Specific (ML, Frontend, Infra)

These questions are tailored to your specific track and test your depth in your chosen domain.

• Frontend: Build a reusable, highly performant data-grid component in React that can handle 100,000 rows of live-updating data.
• Infra: Explain how you would design a multi-region active-active deployment architecture in AWS.
• ML/Perception: Describe the trade-offs between different techniques for handling class imbalance in a behavior prediction dataset.
• OS: Walk me through the process of writing a custom device driver for a new hardware sensor.

Behavioral and Leadership

These questions assess your cultural fit, resilience, and ability to work within a team. Use the STAR method to structure your answers.

• Tell me about a time you had to deliver a critical project with tight deadlines and shifting requirements.
• Describe a situation where you identified a major architectural flaw in a system. How did you convince the team to address it?
• Walk me through a time when you mentored a junior engineer who was struggling with a complex task.
• Tell me about a time you made a significant mistake in production. What was the impact, and what did you learn?
• Describe a project where you had to collaborate closely with a team outside of engineering (e.g., product, operations, or hardware).

Frequently Asked Questions

Q: How difficult is the technical interview process, and how long should I prepare? The process is rigorous and highly calibrated. Most successful candidates spend 4 to 8 weeks preparing, focusing heavily on algorithmic problem-solving (LeetCode Medium/Hard) and practicing mock system design interviews. Consistent, focused preparation is key.

Q: Will I be writing code on a whiteboard or a computer? All coding rounds are currently conducted virtually using a shared, web-based coding environment. You will be expected to write syntactically correct, executable code, though interviewers care more about your logic and problem-solving approach than perfect syntax memory.

Q: How does team matching work? Because & General Intuition hires for specific domains (e.g., Cloud Infrastructure, UI Toolkit, Perception), you are generally interviewing for a specific track. If you pass the general technical bar, you may have follow-up conversations with specific hiring managers to ensure mutual alignment on projects and team culture.

Q: What is the typical timeline from the first recruiter screen to an offer? The end-to-end process typically takes 3 to 6 weeks. This timeline can be accelerated if you have competing offers or impending deadlines. We strive to provide feedback within a few days after your onsite loop.

Q: Are these roles remote, hybrid, or onsite? Work arrangements vary by team and location. Many roles in Mountain View, Sunnyvale, and Ann Arbor operate on a hybrid model to facilitate collaboration with hardware and lab teams, while certain software-only roles (like specific Frontend or IT Operations positions) may offer more flexibility. Clarify this with your recruiter early in the process.

Other General Tips

• Clarify Before You Code: Never start writing code the moment you hear the prompt. Take 2-3 minutes to ask clarifying questions about edge cases, input sizes, and constraints. This demonstrates maturity and prevents you from solving the wrong problem.

• Drive the System Design Interview: Do not wait for the interviewer to prompt you for the next step. A strong candidate outlines the API, sketches the high-level architecture, and proactively dives into bottlenecks and scaling strategies.
• Tailor Your Behavioral Examples: Choose stories that highlight your impact on the business, your ability to handle ambiguity, and your cross-functional collaboration. & General Intuition values engineers who think about the end-user and the broader system, not just their isolated codebase.

• Brush Up on Your Primary Language: You will be expected to know the standard libraries, memory management quirks, and performance implications of the language you choose to interview in. Do not switch to a language you are less familiar with just because you think it looks better.

Summary & Next Steps

Joining & General Intuition as a Software Engineer is a unique opportunity to build the foundational technologies that drive the future of autonomous systems and AI tooling. You will be surrounded by exceptionally talented peers, tackling problems that demand creativity, rigor, and a deep understanding of computer science principles at scale.

To succeed in this interview loop, focus your preparation on mastering core data structures and algorithms, practicing comprehensive system design, and polishing your behavioral narratives. Remember that interviewers are looking for a colleague, not just a coder. Show them how you think, how you communicate, and how you adapt to new technical constraints on the fly.

The compensation data above reflects the broad spectrum of Software Engineering roles at & General Intuition, ranging from early-career frontend positions to highly specialized senior ML and Operating Systems roles across various geographic markets. Your specific offer will be heavily dependent on your leveled seniority, your specialized domain, and your location. Use this data to understand the market, but focus your immediate energy on passing the technical bar.

You have the skills and the capability to excel in this process. Approach your preparation strategically, practice communicating your technical decisions clearly, and go into your interviews with confidence. For more insights, practice questions, and interview strategies, continue exploring the resources available on Dataford. Good luck—you are going to do great!