On July 25th, I interviewed with an AI company for a Founding Senior Backend Engineer role. They’re building an agentic AI platform designed to empower recruiters—automating everything from sourcing and screening to evaluation with remarkable speed and consistency. Their flagship product, RB, is already in production with real traction.
Interview Context
The conversation was with Chief Business Officer and the hiring team. It ran for 38 minutes and was one of the more engaging interviews I’ve had. Both interviewers were alert, curious, and responsive—especially when I shared war stories from past engineering projects. This post will break down how the interview went, what I did well, and how I can level up for the next round.
What Went Well
Strong Technical Storytelling
When asked about my backend experience, I jumped right into a project I was proud of—a Media Planner app I built at Kaizen Apps using TypeScript, MongoDB, Next.js, and Auth0. I described the architectural decisions (like SWR for caching with plans to integrate Redis), and how the system improved team productivity by automating and simplifying campaign management workflows.
💡 Takeaway: I kept the focus on impact and architecture, which kept the energy high and the interviewers engaged.
Demonstrated Adaptability & Ownership
I shared two stories to highlight my approach to ambiguity:
- In one case, I convinced leadership to greenlight a hidden “secret project” to replace a subpar product design—and it ended up impressing investors.
- In another, I worked closely with a CTO to design an enterprise data warehouse for ad campaign analytics, navigating vague requirements through constant collaboration, architecture diagrams, and iterative standups.
These anecdotes showcased my ability to self-direct, communicate, and execute under uncertainty—all critical traits for a founding engineer.
Cultural Fit & Passion for Building
They asked why I was interested in Neuroscale, and my response was honest: AI is changing everything. I love building things from scratch, especially with agentic AI systems. I emphasized my startup experience and desire to grow my skills across a diverse tech stack—which resonated with their vision.
When Vijay asked how I felt about joining a high-speed team and potentially leading one, I lit up. I explained how I enjoy mentoring other devs, doing code reviews, pair programming, and scaling systems fast. They seemed genuinely pleased by my enthusiasm.
Technical Questions & My Answers
Here’s a breakdown of what they asked and how I responded:
Question Tell us about a backend system you built recently. I described a scalable campaign planning tool built with TypeScript, MongoDB, SWR, and React/Next. Emphasized scalability, caching, component-based architecture, and real-time data.
Have you worked with clients directly? Yes — I described a real estate project where I improved developer workflows by introducing structured API documentation between front- and back-end teams.
How do you handle vague product requirements? I shared stories where I tackled ambiguity using architecture diagrams, stakeholder communication, and iterative development (2–3 standups per week).
Why leave your current role? After 5 years at Kaizen, I want new challenges and to deepen my technical skills. My mentor told me my only weakness is “lack of time”—so I’m looking to grow through new experiences.
Why our AI company? I love building impactful systems from scratch, and I’m fascinated by agentic AI. The chance to work on a team scaling production AI is right in my wheelhouse.
What are your top 3 tech skills? TypeScript, Postgres/Redis (depending on the use case), and REST API design. I also mentioned proficiency in AWS/Azure and some DevOps experience.
Do you contribute to communities? Yes — I helped a Ukrainian team build a drone simulator with Unreal Engine + Microsoft AirSIM, and created a SPA to support their MVP.
Any AI projects? Yes — I built a personalized health recommendation system using OpenHealth and prototyped a generative UI tool that builds front-end designs from prompts.
Interviewer Feedback
There was no formal feedback, but I noticed some positive cues:
- They laughed at some of my analogies (e.g., replacing a “person for an API call”).
- They nodded and encouraged me when I detailed my past work leading dev teams and solving messy, real-world product issues.
- They said multiple times that they “enjoyed the conversation.”
- At the end, they told me they were considering me for the next round: a 2-hour technical interview covering bug fixing, system design, and hands-on problem-solving.
That was a solid signal of interest.
What I Can Improve
While the conversation went well overall, there are a few areas to tighten up:
Simplify My Stories
I tend to go into technical detail quickly, and while that’s great for depth, I should streamline my storytelling using the STAR format (Situation, Task, Action, Result). That keeps the pacing smooth and helps non-technical interviewers stay engaged.
Preempt Salary Discussions
Instead of waiting for the salary context, I could prep a more structured answer, stating my range but anchoring it with my value and experience.
Clarify My Role in Projects
In one story, I mixed “founding engineer” and “full stack dev” a bit too fluidly. I need to be more explicit about my role and responsibilities in each project to give a clearer picture of ownership.
Final Thoughts
This interview reminded me why I love what I do.
The AI company is a sharp, ambitious team, and the opportunity to build with them—alongside founders, researchers, and high-velocity engineers—is exactly the kind of challenge I’m chasing. Whether it’s refining a backend architecture, scaling new AI systems, or mentoring younger devs, I’m ready to bring energy, focus, and grit.
Looking forward to Round 2. Let’s build something world-changing.