Okay, I've searched for Senior Software Engineer roles in the United States that are full-time, require 7+ years of experience, involve AI or machine learning technologies, and include disability insurance benefits. I have found 152 positions matching these criteria for you.

Sure. Here's the analysis:

Job Analysis:

The Senior Software Engineer role at Karat fundamentally aims to build and evolve a cutting-edge, AI-enhanced interviewing platform that transforms how technical talent is assessed, making it more predictive, inclusive, and fair. This position is not just about writing code; it’s about architecting full-stack solutions that balance innovation with reliability in a production environment serving enterprise clients. The candidate will regularly confront complex challenges such as integrating AI/ML technologies—especially large language models (LLMs)—to enhance user experience and platform intelligence. Success means delivering scalable, secure, and high-performance systems while collaborating across product, design, and data science teams to translate broad visions into concrete, maintainable solutions. Given the seniority, the role requires technical leadership, mentorship, and influencing architectural decisions, ensuring the balance between short-term feature delivery and long-term system health. The ideal candidate combines deep proficiency in languages like Ruby, Python, or TypeScript, strong system architecture skills, and cloud infrastructure experience with the ability to communicate effectively across diverse stakeholders. They must also demonstrate an appreciation for fairness and inclusion in technical interviewing, aligning technical craftsmanship with the company’s mission-driven focus.

Company Analysis:

Karat operates as an innovative leader in the talent assessment and technical interviewing space, addressing a critical global shortage of software engineers with its unique Interviewing Cloud. Positioned as a transformative technology and services platform blending human expertise with AI, Karat holds strong market trust from high-profile enterprise clients like Roblox and American Express. The company culture, inferred from its mission and benefits, is inclusive, employee-centric, and highly collaborative, valuing technical innovation tied directly to social impact—eliminating bias and expanding access to underrepresented candidates. The Engineering team embodies a remote-first and distributed structure but demands deep cross-functional collaboration to ensure the platform’s constant evolution and enterprise-grade reliability. For a Senior Software Engineer, this environment presents both opportunity and challenge: the role has high visibility within technical leadership circles and directly supports strategic goals of scale, fairness, and product excellence. As a strategic hire, this position helps drive foundational AI-driven product features critical for Karat’s continued growth and differentiation in a competitive hiring landscape. Candidates must thrive in an environment that balances rapid iteration with technical rigor and share a passion for reimagining the future of hiring.

Absolutely. Here are some mock interview questions that could come up:

• Behavioral: Tell me about a time when you led a technical initiative that involved integrating AI or ML into an existing product. What challenges did you face and how did you address them?
• Behavioral: Describe an experience where you had to balance competing priorities between short-term feature delivery and long-term system architecture improvements. How did you navigate this?
• Behavioral: Share an example of how you have mentored or influenced junior engineers or peers to improve code quality or adopt best practices.
• Behavioral: Can you give an example of working effectively in a cross-functional team with non-engineering stakeholders? How did you ensure clear communication on complex technical topics?
• Technical: Explain your approach to designing scalable full-stack systems that incorporate AI capabilities. What architectural principles guide your decisions?
• Technical: How have you worked with LLM APIs or knowledge-enhanced language model pipelines in a past project? What metrics or feedback loops did you use to improve AI feature performance?
• Technical: Discuss your experience with cloud infrastructure and deployment strategies (AWS, GCP, Azure) in supporting production-grade applications.
• Technical: How do you design and implement REST and GraphQL APIs to serve diverse user groups such as interviewers, candidates, and hiring managers?
• Situational: Imagine a cross-team conflict arises about whether to prioritize a quick AI feature rollout or refactoring critical infrastructure for stability. How would you approach resolving this?
• Situational: You receive feedback from users that a newly released AI-driven assessment feature is showing biases. How would you investigate and respond to this situation?
• Situational: Midway through a project, a shift in product direction requires rapid changes to the platform that may impact technical debt. How do you balance delivery with quality?
• Company Fit: What motivates you about Karat’s mission to create more predictive and fair technical interviewing experiences?
• Company Fit: How do you see your expertise in AI and software engineering contributing to solving the global software engineering talent shortage?
• Company Fit: Karat operates in a remote and distributed environment. What strategies do you use to remain productive and engaged within such a work culture?
• Questions for Interviewer: How does Karat balance innovation speed with ensuring enterprise-grade platform reliability and security?
• Questions for Interviewer: What are the immediate technical challenges the engineering team is facing related to AI integration on the interviewing platform?
• Questions for Interviewer: Can you describe how cross-functional collaboration works here between engineering, product, and data science teams?