avyfain

You can even imagine a second order agent with an outer loop assessing tasks, and smaller luna/sonnet level ones performing. You could even have the meta task of assessing task ROI as a task on the board!

[0]: https://faingezicht.com/articles/2026/05/28/shape-of-what-we...

AngelList's mission is to accelerate innovation by providing startups and investors with the tools they need to succeed. We have the world’s largest early-stage venture portfolio with $17B+ assets under management and $124B+ on our platform, delivering capital to over 12,000 startups. We work with some of the best emerging fund managers to ensure every deserving startup has access to capital.

I was hired into the role from one of these HN threads last summer. One of the things that attracted me most was the density of former founders and aspiring entrepreneurs on the team.

We're hiring full-stack engineers with experience building web applications at scale. Fintech knowledge is a plus, but not required.

I'm the hiring manager for our Funds Engineering team[0]. We’re building the data layer that powers our general ledger. We work on some of the most interesting datasets out there: We model capital flows in the venture ecosystem to understand where value accrues and, ultimately, which investors and founders win or lose.

I'd be happy to talk about these roles, about any open role we have at AngelList[1], or any questions you might about working here.

[0]: https://www.angellist.com/careers/9870a63b-ac75-436b-b1a6-a2... [1]: https://www.angellist.com/careers#open-positions

AngelList's mission is to accelerate innovation by providing startups and investors with the tools they need to succeed. We have the world’s largest early-stage venture portfolio with $17B+ assets under management and $124B+ on our platform, delivering capital to over 12,000 startups. We work with some of the best emerging fund managers to ensure every deserving startup has access to capital.

I was hired into the role from one of these HN threads last summer. One of the things that attracted me most was the density of former founders and aspiring entrepreneurs on the team.

We're hiring full-stack engineers with experience building web applications at scale. Fintech knowledge is a plus, but not required.

I'm the hiring manager for two senior roles on our Funds Engineering team. We’re building the data layer that powers our general ledger. We work on some of the most interesting datasets out there: We model capital flows in the venture ecosystem to understand where value accrues and, ultimately, which investors and founders win or lose.

I'd be happy to talk about these roles, about any open role we have at AngelList (https://www.angellist.com/careers#open-positions), or any questions you might about working here.

Yes, but also more stale code from old versions which use patterns that the community has for various reasons moved on from. I ran into a lot of trouble with deprecated patterns while teaching myself react last year with assistants on the side. React 17 and prior version patterns kept coming up all the time.

Location: San Francisco, CA

Remote: No

Willing to relocate: No

Technologies: AI/ML (Entity Resolution, Knowledge Graphs, Search, LLMs, Predictive Models), Data Engineering (Warehousing, Orchestration, Analytics, A/B Experimentation, ETL/ELT, Visualization), Fullstack Software Engineering. Most recent experience on Python/JavaScript/DuckDB on AWS but worked professionally with Ruby, Scala, Java, Go, TypeScript, R, SQL, dbt, Snowflake, Postgres, Solr, Cassandra, Hadoop, Spark, Airflow, Docker, etc.

Résumé/CV: https://www.linkedin.com/in/avyfaingezicht/ or more info on request

Email: avy at faingezicht.com

10+ years of experience building data heavy products, both as an IC and EM.

Looking for eng management or player/coach roles at growing startups. Excited to wear many hats. I'm ex-Apple, and a former founder.

Location: San Francisco, CA

Remote: No

Willing to relocate: No

Technologies: AI/ML (Entity Resolution, Knowledge Graphs, Search, LLMs, Predictive Models), Data Engineering (Warehousing, Orchestration, Analytics, A/B Experimentation, ETL/ELT, Visualization), Fullstack Software Engineering. Most recent experience on Python/JavaScript/DuckDB on AWS but worked professionally with Ruby, Scala, Java, Go, TypeScript, R, SQL, dbt, Snowflake, Postgres, Solr, Cassandra, Hadoop, Spark, Airflow, Docker, etc.

Résumé/CV: https://www.linkedin.com/in/avyfaingezicht/ or more info on request

Email: avy at faingezicht.com

10+ years of experience building data heavy products, both as an IC and EM.

Looking for eng management or player/coach roles at growing startups. Excited to wear many hats. I'm ex-Apple, and a former founder.

I'm Avy, CTO and co-founder at [InScope](https://inscopehq.com), where we're creating a financial data platform that gives accounting teams super-powers. My co-founders, Mary and Kelsey, suffered many audits first-hand as finance and accounting leaders at high-growth tech companies like Flexport, Miro, Yelp, and Dropbox.

Join us as our first AI Engineer, our first Designer, or our second Fullstack Engineer (all SF-based). We’ve signed customers, raised a seed round from top investors, and are heads-down building.

Today, finance teams prepare for their audits using Word, Excel, and a whole lot of human effort. We're seeking to change that with software.

All roles will be fast-paced: You will set up systems from scratch, solve a mix of full stack product problems, and build AI-infused data workflows. Our early prototypes are built with Python, JS, React, dbt, and DuckDB, all on AWS. You'll help us choose our production stack.

Would love to chat if you're curious to learn more.

Send me a note at avy@<the-domain-listed-above>, or check out the full JDs here:

* [Founding Fullstack Engineer](https://inscope.notion.site/Founding-Engineer-Full-Stack-InS...)

* [Founding AI Engineer](https://inscope.notion.site/Founding-AI-Engineer-InScope-140...)

* [Founding Product Designer](https://inscope.notion.site/Founding-Product-Designer-InScop...)

TLDR, the essay explores how LLM could evolve into front-end routers that connect users with specialized tools, leading to a future where federated models determine the best-suited system to answer specific queries. Not too different from today's federated search approaches.

I'm Avy, CTO and co-founder at [InScope](https://inscopehq.com), where we're automating financial statements and audits. My co-founders, Mary and Kelsey, suffered many audits first-hand as finance and accounting leaders at high-growth tech companies like Flexport, Miro, Yelp, and Dropbox.

Investors and other stakeholders require audited financials from private companies that hit certain growth milestones, ensuring the health of the company before they can receive funding or raise debt. Today, finance teams prepare for their audits using Word, Excel, and a whole lot of human effort. We're seeking to change that with software.

We are participating in Better Tomorrow Ventures' fintech accelerator and are looking for an experienced founding engineer. The role will be fast-paced: You will set up systems from scratch, solve a mix of full stack product engineering problems, and build AI-infused data workflows. Our early prototypes are built with Python, Typescript, React, dbt, and DuckDB, but you'll help us choose our production stack.

We believe in distributed teams and will be flexible about remote work, but early-on we expect you to be based in San Francisco to allow for fast collaboration cycles.

Send me a note at avy@<the-domain-listed-above>, or you can find more info here: https://www.notion.so/Founding-Engineer-Full-Stack-35060b2a2...

I'm Avy, CTO and co-founder at [InScope](https://inscopehq.com), where we're automating financial statements and audits. My co-founders, Mary and Kelsey, suffered many audits first-hand as finance and accounting leaders at high-growth tech companies like Flexport, Miro, Yelp, and Dropbox.

Investors and other stakeholders require audited financials from every private company that hits certain growth milestones, ensuring the health of the company before they can receive funding or raise debt. Today, finance teams prepare for their audits using Word, Excel, and a whole lot of human effort. We're seeking to change that with software.

We are participating in Better Tomorrow Ventures' fintech accelerator and are looking for a senior founding engineer. The role will be fast-paced: You will set up systems from scratch, solve a mix of full stack product engineering problems, and build AI-infused data workflows. Our early prototypes are built with Python, React, dbt, and DuckDB, but you'll help us choose our production stack.

We believe in distributed teams and will be flexible about remote work, but early-on we expect you to be based in San Francisco to allow for fast collaboration cycles.

Send me a note at avy@<the-domain-listed-above>, or you can find more info here: https://www.notion.so/inscope/Founding-Engineer-Full-Stack-3...

I write very little these days, but you can find a mix of tech and economics, as well as a selection of my photography (mostly travel and street photo).

For the HN crowd, I’d highlight my piece on evaluating startup offers: https://faingezicht.com/articles/2021/09/20/evaluating-start...

We are hiring Senior Analytics Engineers, Software Engineers, Analysts, and several roles in the GTM side of the house. Our team has a hybrid remote set up, with offices in SF and Chicago, and many roles fully remote. Check out our open roles: https://www.vouch.us/careers

I joined a year and a half ago to lead our data efforts after 6 years at Apple, and it's been a great experience. I wrote a bit about why here[1]. Our roadmap is full of interesting technical problems - from building the most comprehensive startup ecosystem dataset in the world to embedded insurance platform challenges, which I recently covered in our engineering blog[2].

Apply directly on the link above, or feel free to ping me at avy.faingezicht@<our domain> and I'd be happy to share more about what we're building or route you to the right hiring manager.

[0] https://techcrunch.com/2021/09/10/vouch-business-insurance-p... [1] https://faingezicht.com/articles/2021/04/26/new-beginnings/ [2] https://medium.com/vouch-engineering/why-should-engineers-ca...

More info and recommendations/reviews: https://faingezicht.com/book_pipe/

Vouch is building an insurance company that can keep up with the rapid change that characterizes the startup lifecycle. We're doing this by making insurance fast, responsive, and focused on our customer - startups. Our team is currently 150+ people and we're planning on doubling over the next year. The engineering team (currently ~40 people) moves fast, and we see each person as crucial to the success of the company. We've raised over $160M from YCombinator, Ribbit Capital, etc[0] and partner closely with Silicon Valley Bank and other key players in the space.

We are hiring Senior Engineers and Engineering Managers across our Data, Platform, Customer Experience, and Enablement teams. Our team has a hybrid remote set up, with offices in SF and Chicago, and many roles fully remote. Check out our open roles: https://www.vouch.us/careers

I joined almost a year ago to lead our data efforts after 6 years at Apple, and it's been a great experience. I wrote a bit about why here[1]. Our roadmap is full of interesting technical problems - from building the most comprehensive startup ecosystem dataset in the world to embedded insurance platform challenges.

Feel free to ping me at avy.faingezicht@<our domain> and I'd be happy to share more about what we're building or route you to the right hiring manager.

[0] https://techcrunch.com/2021/09/10/vouch-business-insurance-p...

[1] https://faingezicht.com/articles/2021/04/26/new-beginnings/

Agreed that liquidation preference would be helpful, too, but if at the time you're signing on you think the liquidation preference will come into play you shouldn't join them.

Left FAANG knowing that money would be better there. My new opportunity is (so far) a lot more fun, a I'm learning a lot more about the things I want to learn.

I'm planning to write a more advanced version of this article in a few months, discussing tax implications, the "should I exercise my options" question, etc.

> could be more helpful if it included more realistic numbers.

Any ideas on where to find these? While there's a lot of info out there on valuations most datasets have the problem of hindsight bias, especially missing data at the pre-A round.

> only 2 startups are compared in the NPV calculation. What about joining a BigCo / FAANG?

My original model was actually a FAANG vs two startup model (I left Apple) but it gets too complex to try to explain it in a post that's aimed at the stock options 101 crowd.

> the math gets slightly better if you assume you leave after some amount of vesting.

100%, although that's tough to model without just adding an arbitrary cutoff.

> https://tldroptions.io/

Thanks, I did not know about this tool!

Got any questions about what our day to day is like, what we are working on, or our team's technical vision? We're growing our data and engineering teams - if you've got questions, I'm happy to answer.

Another one I'd recommend if you enjoyed those two, although in a very different vein is Bloom's Moralities of Everyday Life, which is supposedly a psychology course, but really goes into comparative culture questions that IMO make it closer to an anthropology course. https://www.coursera.org/learn/moralities