What is a Software Engineer at Cognition?

At Cognition, a Software Engineer is not just a contributor to a codebase; you are an architect of the future of software development itself. As the creators of Devin (the first AI software engineer) and Windsurf (the AI-native IDE), the team is tackling one of the most ambitious challenges in technology: building AI agents that can reason, code, and collaborate like human engineers.

This role places you at the center of a "talent-dense" environment. The founding team includes world-class competitive programmers and leaders from Scale AI, Google DeepMind, and Waymo. Whether you are applying as a Product Engineer focused on UX, a Delta Engineer handling complex enterprise deployments, or a core Systems Engineer, your work directly impacts how developers worldwide will interact with AI. You are building the tools that will empower other engineers to solve harder problems, faster.

You should expect a high-intensity, high-agency environment. Cognition values a "founder mindset"—the ability to punch through technical walls, navigate ambiguity, and ship products that delight users immediately. You aren't just writing features; you are defining the primitives of AI-assisted engineering.

Getting Ready for Your Interviews

Preparing for an interview at Cognition requires a shift in mindset. While standard coding proficiency is a baseline, the team looks for "spikes" in ability—exceptional talent in specific areas like competitive programming, systems architecture, or product intuition.

Technical Depth & Speed Cognition’s DNA is rooted in competitive programming and rigorous engineering. You will be evaluated on your ability to write correct, efficient code quickly. Interviewers look for candidates who can navigate complex logic puzzles and algorithmic challenges with fluency.

Builder Mentality Theoretical knowledge is secondary to practical application. You must demonstrate that you can take an abstract problem and "ship it." For Product roles, this means showing deep empathy for the user experience. For Delta roles, it means debugging what no one else can figure out. You need to show you would rather build a solution than wait for one.

Adaptability & Learning The AI landscape changes weekly. You will be assessed on your slope—how fast you learn. Interviewers want to see how you handle unfamiliar codebases, ambiguous requirements, and the pressure of a fast-moving startup environment.

Founder Mindset This is a core value. You will be evaluated on your sense of ownership. Do you wait for instructions, or do you identify pain points and solve them? Be ready to discuss times you took initiative beyond your defined scope.

Interview Process Overview

The interview process at Cognition is designed to identify engineers who can operate at a high level of technical rigor while maintaining the speed required by an early-stage AI lab. The process is streamlined but intense, often moving faster than big-tech loops.

Generally, you will begin with a recruiter screen or a chat with a hiring manager to align on your background and interest in the AI agent space. This is followed by a technical screen, which is notoriously challenging. Given the team's background in competitive programming (IOI/ICPC), expect the coding bar to be high. You won't just be asked to solve a problem; you will be expected to solve it efficiently and cleanly.

The onsite stage (often conducted virtually or in the San Francisco office) involves a mix of deep technical rounds and culture-fit discussions. You will face rounds focused on algorithmic problem solving, practical system design (often related to building tools or agents), and potentially a "debugging" or "forward-deployed" scenario depending on the specific role (e.g., Delta Engineer). The final steps often involve a conversation with founders to assess your "high agency" and alignment with the mission.

This timeline illustrates a standard flow, but Cognition is known to move quickly for top talent. Use the time between the technical screen and the onsite to sharpen your algorithmic skills and familiarize yourself with the unique challenges of building LLM-based applications and developer tools.

Deep Dive into Evaluation Areas

Cognition evaluates candidates on their ability to reason through complex problems from first principles. The following areas are critical for success.

Algorithmic Problem Solving & Coding

Because the team comprises former competitive programmers, this is the most rigorous part of the assessment. You are expected to write bug-free code that handles edge cases gracefully.

Be ready to go over:

• Complex Data Structures: Trees, Graphs, Tries, and Hash Maps.
• Dynamic Programming: optimizing for time and space complexity.
• Recursion and Backtracking: essential for reasoning about agent decision trees.
• String Manipulation: parsing and processing code (relevant to building an IDE).

Example questions or scenarios:

• "Given a stream of code edits, efficiently reconstruct the final file state."
• "Implement a custom parser for a simplified programming language."
• "Find the shortest path in a graph with dynamic edge weights."

Systems Design & Architecture

For core engineering and Delta roles, you need to show you can build scalable, robust systems. The focus is often on practical application rather than abstract high-level design.

Be ready to go over:

• API Design: Creating clean, intuitive interfaces for agents to interact with.
• Concurrency & Latency: Handling real-time updates in an IDE environment (Windsurf).
• Distributed Systems: Managing state across distributed AI agents.
• Security: Sandboxing code execution (crucial for Devin).

Example questions or scenarios:

• "Design a system that allows an AI agent to safely execute user code in a sandbox."
• "How would you architect a real-time collaborative code editor?"
• "Design the logging and retrieval system for an agent's long-running task history."

Product Instinct & User Empathy

Especially for Product Engineer roles, you must bridge the gap between complex AI and a delightful user experience. You need to show you can make product decisions while coding.

Be ready to go over:

• UI/UX Polish: "First minute magic" and reducing friction.
• Frontend Technologies: Proficiency in React, TypeScript, and state management.
• User Feedback Loops: Translating user pain into technical requirements.

Example questions or scenarios:

• "How would you design the feedback mechanism for Devin when it makes a mistake?"
• "Critique a developer tool you use daily. How would you improve its UX using AI?"

Debugging & "Delta" Engineering

For Delta Engineer roles, the focus is on debugging the impossible and integrating with complex enterprise environments.

Be ready to go over:

• Codebase Navigation: Quickly understanding unfamiliar code.
• Root Cause Analysis: Debugging issues across the stack (network, application, infrastructure).
• Integration Logic: Connecting Cognition’s APIs with legacy enterprise systems.

Example questions or scenarios:

• "A customer's deployment is failing intermittently with no clear error logs. How do you debug this?"
• "Walk me through how you would reverse-engineer an undocumented API."

Key Responsibilities

As a Software Engineer at Cognition, your day-to-day work is a blend of intense engineering and strategic product development. You are not just maintaining a service; you are building the "brain" of an AI software engineer.

You will likely own end-to-end features for Devin or Windsurf. This means scoping the requirements, designing the architecture, implementing the solution (often in Python or TypeScript), and refining the UX based on user feedback. For Product Engineers, this involves pushing the boundaries of how developers interact with agents—creating "performant and beautiful experiences."

Collaboration is tight-knit. You will work closely with the founding team and other high-caliber engineers to "punch through technical walls." Whether it's optimizing the inference latency of an LLM call or designing a new way for Devin to visualize its thought process, you are expected to operate with autonomy.

For Delta Engineers, the responsibility extends to the field. You will own the technical success of strategic accounts, architecting deployments, and bringing insights back to the core engineering team. You act as the bridge between the "product edge" and the core platform.

Role Requirements & Qualifications

Cognition is looking for engineers who have a track record of pursuing excellence. The bar is high, and the requirements reflect a need for both raw intelligence and practical "get-it-done" ability.

• Strong Engineering Foundation: A degree in CS or equivalent is common, but a history of competitive programming (IOI, ICPC, Codeforces) is highly valued and often serves as a proxy for the required technical depth.
• Proficiency in the Stack: You should be comfortable with Python and TypeScript. Experience with React is essential for product-focused roles.
• Builder Track Record: You need to have built and shipped software. Former founders or early employees at high-growth startups often excel here.
• Ambiguity Tolerance: You must be comfortable navigating unfamiliar codebases and solving open-ended problems without a clear roadmap.

Nice-to-have skills:

• Experience building developer tools (IDEs, CLIs, CI/CD).
• Deep knowledge of LLMs, agents, and AI application architectures.
• Experience with enterprise infrastructure (security, networking, on-prem deployments).

Common Interview Questions

These questions reflect the "builder" and "problem solver" DNA of Cognition. They are designed to test your ability to think on your feet and your depth of technical understanding.

Coding & Algorithms

• "Given a directory of files, implement a function to find all duplicate files based on content, not name."
• "Implement an autocomplete system for a code editor. How do you optimize for latency?"
• "Solve the 'Trapping Rain Water' problem." (Standard hard algorithmic questions are fair game).
• "Parse a mathematical expression string and evaluate it, handling operator precedence."

System Design & Applied AI

• "Design a system to index a large codebase for semantic search."
• "How would you architect a secure sandbox for running untrusted Python code?"
• "Design a real-time diffing algorithm to show changes between two versions of a file."
• "How do you handle context window limits when feeding a large repo into an LLM?"

Behavioral & Culture

• "Tell me about a time you had to learn a new technology over a weekend to ship a feature."
• "Describe a technical problem you solved that no one else could figure out."
• "If you were the CEO of your last company, what is one thing you would have changed immediately?"
• "What is the most impressive thing you have built from scratch?"

These questions are based on real interview experiences from candidates who interviewed at this company. You can practice answering them interactively on Dataford to better prepare for your interview.

Frequently Asked Questions

Q: How important is competitive programming experience? While not a strict requirement, the team values the algorithmic speed and correctness that comes from that background. If you don't have it, ensure your command of data structures and algorithms is exceptionally strong.

Q: Is this a remote role? Cognition places a high value on in-person collaboration. Most roles, especially engineering, are expected to be onsite in San Francisco to foster the tight feedback loops required for this stage of innovation.

Q: What is the difference between a Product Engineer and a Delta Engineer? A Product Engineer focuses on the core user experience, UI, and feature set of Devin/Windsurf. A Delta Engineer is more akin to a high-level Forward Deployed Engineer, focusing on customer implementations, complex integrations, and bringing field feedback to the product team.

Q: How technical are the interviews? Very. Even for roles with a product or commercial slant, you are expected to be a strong coder. There are no "non-technical" engineering roles here.

Q: What is the work-life balance like? The company describes itself as "high intensity" and "fast-moving." Candidates who excel are typically those who enjoy "grinding" on hard problems and are ambitious about their impact.

Other General Tips

Show, Don't Just Tell Cognition loves builders. If you have side projects, open-source contributions, or tools you've built to solve your own problems, bring them up. Being able to discuss the architectural trade-offs of a personal project can be more impressive than a standard system design answer.

Speed is a Feature In the interview, aim for a working solution quickly, then optimize. The team iterates fast, and they want to see that you can get to a "MVP" mental model rapidly without getting bogged down in analysis paralysis.

Demonstrate User Empathy Even in deep technical rounds, mentioning the user experience sets you apart. If you are designing an API, ask how the developer will use it. If you are building a backend service, ask how it impacts the frontend latency.

Be Honest About What You Don't Know The team values "high slope" learners. If you don't know a specific technology, admit it, but then explain how you would figure it out. Walk them through your research and debugging process.

Summary & Next Steps

Becoming a Software Engineer at Cognition means joining a team that is redefining the software development lifecycle. You will be working alongside some of the brightest minds in the industry to build Devin and Windsurf, tools that are already changing how code is written. The role demands high technical agency, a love for hard problems, and the ability to ship product-grade solutions at startup speed.

To succeed, focus your preparation on algorithmic fluency, system design for developer tools, and demonstrating a founder-like ownership of your work. Review your past projects to identify moments where you punched above your weight or solved ambiguous problems. This is your chance to help build the AI teammates of the future.

The compensation at Cognition is competitive with top-tier AI labs, typically including a strong base salary and significant equity upside. The wide range in base salary often reflects the leveling (e.g., Product Engineer vs. Senior Delta Engineer) and the premium placed on specialized skills like competitive programming or AI infrastructure experience.

For more interview insights and resources to help you prepare, explore Dataford. Good luck—go build something amazing.