Reflection on finding a new job after failed at being a founder

After a failed attempt to start a company, I was, for the 4th time, active in the job market with 8.5 years of experience under my belt. The search took 5 weeks, during which I chatted with 18 companies, received 3 offers, 3 rejections, was ghosted by 1, and withdrew from the rest at various stages. In terms of outcome, I’ll be joining Anthropic to be a founding member of its Claude Growth team.

In this post, I’d like to document my thought process during my job search. I believe this will be valuable to me, if not to anyone else, in the future.

What Made This Job Search Unique

This job search was special in 2 aspects:

Thanks to generative AI, the entire tech industry and software engineering jobs (in their broad sense, encompassing MLEs, DS, and others) are experiencing an extremely rapid paradigm shift. ChatGPT has been around for two years, DeepSeek was hailed as the AI Sputnik moment for the US, and predictions like “AI will write 90% of code in a few months” have been circulated.
I recently spent a year as a startup founder, which didn’t turn out as desired. Before becoming a founder, I had understood that such an experience shouldn’t negatively affect my career. However, I didn’t fully comprehend what kind of impact it might have, if not negative. Surprisingly, it led me to join a growth team, which is a significant departure from my previous experience as a backend engineer.

The Impact of AI

Thanks to DeepSeek, I’ve had some thoughts on the trajectory of AI: I believe that the scaling law will persist for some time, even though it may no longer solely rely on scaling pre-training. Consequently, we will likely soon have 2X-5X AI capabilities, if not 10X-100X. Meanwhile, AI’s transformative power runs so deep and wide that forecasting specific developments remains elusive – the only certainty is that we face profound and revolutionary changes ahead.

DeepSeek has made the GPT-4/4o equivalent generation of models commodities. These models are already incredibly capable and their costs are rapidly decreasing. This has already prompted foundational model companies to invest more in the application layer (OpenAI’s Operator and Deep Research, Anthropic’s Claude Code and MCP). I predict that 2025 will be a year of significant growth for AI applications, benefiting both consumers and enterprises.

Because of these hypotheses, I had 2 expectations for my ideal job:

It must be close to the source and center of AI impact, which means companies that create frontier models (Google, Meta, OpenAI, Anthropic) or companies that develop products that otherwise wouldn’t exist without AI (Perplexity, Cursor, and all sorts of agent companies).
I wanted my role to be closer to product development, ideally with direct visibility of users, sales, marketing, in addition to engineering.

How Being an Ex-Founder Shaped My Path

For Anthropic, I applied for a role in the Labs team, which is responsible for prototyping new applications of Claude models, again, as an investment into the application layer. Both MCP and Claude Code were invented by the Labs team. It sounded like a great match given my interests in exploring AI applications and my recent experience as a founder, which involved quickly prototyping and validating new ideas.

For some reason, by the time my interview got to the hiring manager stage, I was instead being evaluated as an engineer for the Claude Code team, which didn’t seem to be a good fit given my lack of experience in developer tooling. Then, to my surprise, it was suggested that I could be a good fit for the Claude Growth team, particularly because of my experience as a founder.

I’ll admit—I initially approached the Growth team opportunity with skepticism. My misconception painted growth engineering as a peripheral function focused on superficial product tweaks rather than core innovation. But deeper research completely transformed my perspective. Growth sits at the powerful crossroads of product strategy, engineering, and marketing—precisely the nexus I needed to explore. The strategic skillset developed in this role addresses exactly what I found myself lacking as a founder. While I plan to write a dedicated post on why growth teams are crucial (especially for consumer applications), I’m now convinced this role provides the perfect foundation for my future entrepreneurial ambitions.

After the decision, a friend asked whether I regret not staying in the deep learning research field; otherwise, I might be able to work directly on the models as a researcher. It’s a question I asked myself several times, and I think the answer is no. Well, sure, I may be able to have higher pay if I had kept doing deep learning research, but the fact that I chose not to do a PhD at CMU and to have left the research field and moved closer to product shows where my interests really lie. Plus, how could anyone, except the visionary/lucky few people, anticipate the ChatGPT moment? What if Gen AI didn’t break through? My long-term goal, as it has been clear for the last 5 years, is still founding my own company, and I’d like to think I’m on the right track.

Additional Reflections

Support Network

I received numerous helps and supports from my network, including past colleagues, friends, recruiters, investors, not only for the job search itself but also for emotional support, backchanneling, and for just having intellectually interesting conversations. I’ve never been the best at extending and maintaining networks, but it’s reassuring to know that people are willing to help out just because I was trying to be the best version of myself.

The Evolution of Interviews

As I have become more senior, I can feel that I’m assessed A LOT more on behavioral rounds, more on the system design rounds, and a bit less on the coding rounds. Most coding and design questions are practical and relevant to the hiring role. I didn’t do a ton of preparation, so I was glad that I was able to solve/answer most of them purely based on my own experience. It pays off to stay hands-on and to stay curious about how things work.

Location and Remote Working

I was quite tired of working from home for 5 years and was particularly looking for companies with a physical office in NYC and with required in-person time. I noticed many people and companies have the same preference, especially for overachieving people who view their career as a high priority. NYC has a good amount of options for both VC-backed startups and big companies, despite still being second to the Bay Area and maybe Seattle too. Not surprisingly, most NYC startups are in the financial service adjacent fields, but there are also some good ones in sales tech and cybersecurity.