We are a small Health Tech / AI automation start-up growing 3x YoY (we just raised our Series A round!) and looking to expand our platform team.
Our core platform consists of a front-end app, back-end API, SDK, and some DevEx tooling. The tech stack consists of AWS, Typescript, NextJS, React, Python, and the Serverless Framework.
We are looking for individuals with experience working as founding engineers in early-stage startups. The ideal candidate should be excited about learning new things, passionate about DevEx/DevProd, and comfortable cutting through ambiguity.
We are a small Health Tech / AI automation start-up growing 3x YoY (we just raised our Series A round!) and looking to expand our platform team.
Our core platform consists of a front-end app, back-end API, SDK, and some DevEx tooling. The tech stack consists of AWS, Typescript, NextJS, React, Python, and the Serverless Framework.
Your voice and expertise will significantly impact our platform’s strategic direction and development.
We are a small Health Tech / AI automation start-up growing 3x YoY and looking to expand our platform team.
Our core platform consists of a front-end app, back-end API, SDK, and some DevEx tooling. The tech stack consists of AWS, Typescript, NextJS, React, Python, Go, and the Serverless Framework.
Your voice and expertise will significantly impact our platform’s strategic direction and development.
Hello, would you accept remote applicants from outside the US but with everything already setup to start working? This field and position is literally what I am looking for :D
We are a small Health Tech / AI automation start-up growing 3x YoY and looking to expand our platform team.
Our core platform consists of a front-end app, back-end API, SDK, and some DevEx tooling. The tech stack consists of AWS, Typescript, NextJS, React, Python, Go, and the Serverless Framework.
Your voice and expertise will significantly impact our platform’s strategic direction and development.
We are a small Health Tech / AI automation start-up that is growing 3x YoY and is looking to expand our platform team.
Our core platform consists of a front-end app, back-end API, SDK, and some DevEx tooling. The tech stack consists of AWS, Typescript, NextJS, React, Python, Go, and the Serverless Framework.
Your voice and expertise will significantly impact our platform’s strategic direction and development.
If you are an engineering or product leader that has worked in an agile/scrum shop, you know the rollercoaster that comes with sprint planning meetings.
As both a participant and a leader, I've been in the trenches and witnessed various approaches to sprint planning—some more effective than others. All too often though, I’ve seen these meetings devolve into chaos, resulting in misaligned priorities and a waste of valuable time.
Through countless iterations and learnings, I’ve developed a process that has helped teams regain focus, enhance collaboration, and achieve great outcomes.
I recently decided to write down those learnings which I'm excited to share in my latest blog post. I cover:
- Four underlying principles that drive successful sprint planning.
- Essential prerequisites to ensure smooth execution.
- Tactical steps to streamline your sprint planning process.
Would love to hear feedback and what has worked well for you when it comes to your agile planning process!
I usually write about whatever I'm practicing and learning at the moment. My topics have included coding tips in various tech stacks, career growth, ai, web3, hiring, interviewing, knowledge management, leadership and everything in between.
As someone who's been around the tech industry for a while, I know firsthand all the sausage-making that goes into building a great technical hiring funnel.
On the flip side, as a job seeker, I also know how demoralizing it can be to go through a broken hiring process that doesn't accurately reflect your abilities.
With recent layoffs and many talented professionals on the job market, I was compelled to write a blog post about how to build an inclusive hiring culture and find exceptional engineering talent.
If you're involved in your organization's technical hiring process at any stage, I encourage you to give this a read. I share some best practices for conducting effective interviews and improving your own hiring process.
I think structured interviews can be just as easily biased as unbiased. I'm not disagreeing necessarily about being structured with your interview practices, but I find this to be a grey area with promotions also.
As soon as people figure out the check boxes or the structured pointing system they start to check all the boxes, but it doesn't necessarily speak to the nuances between individuals that make them diverse and both valuable. In fact it can lead to a certain type of person people hired or promote, which can be on good characteristics, but I find many times turns into a "certain type" of person.
I guess what I'm saying is structure can take you so far, but you have to be willing to explore a little bit about what makes a person special, and that many times means not controlling the whole interview, and be willing to have your bias challenged through the candidate directing some of it.
Agreed. It's very demoralizing to know that you are extremely capable of doing the job, but since you don't satisfy the narrowly defined fitness function you're being passed into, you fail. But more than that, companies are missing out on great people that may simply have a different way of thinking that isn't accounted for in their structure.
My take-away from interviewing is that as a candidate, getting a "you did not get the job" doesn't change anything. Since I've had the privilege of mostly being employed while interviewing for new jobs, this is a "meh, status quo" thing. Nothing changes, I have no decisions to make. If I get an offer, I have a decision to make.
Does it sting when I get a "No"? Yes, a little, but I did my best and (presumably) someone else did better. So, I take solace in that I did not have to make a (relatively large) decision.
I've also been kinda curious about the research in favor of structured interviews, because as far as I've seen they're generally drawing their conclusions based on "interviewer-predicted performance" vs "actual performance".
How the heck do you measure actual, repeatable performance? Or skill? Income / promotions / etc is very frequently a horrifically biased metric, for similar reasons to interviews, and we have much larger mountains of evidence showing that to be the case. It seems like there's a pretty good chance these studies are just measuring relative bias between interviewers and the interviewee's management, and concluding interviews are done poorly when they disagree with management. i.e. "structured interviews force people to think more like managers" rather than "structured interviews more accurately measure skill".
Using one bad measuring tool to conclude another tool is bad seems... problematic at best. I will grant that "interviews should measure what managers measure" is often what businesses want in bulk, but that does not seem like a particularly good thing to me.
In another comment I was also poking some holes into the “structured” comments, what you say above was in my head but I couldn’t quite articulate it. Well said.
I think checklist interviews miss the mark as you say. You may not have a perfect rubric, but I’m not grading students on a history exam; I am evaluating them for a role in a given position. In the limited time we have to speak, I want to use my intuition and experience as an interviewer and engineer to rapidly get to where the candidate is strong, and where they may have issues.
Project based interviews, even paid, are so frustrating because there is no ROI if you don’t get the job. If I study leetcode, I can apply this skill to interview at a bunch of companies.
I once spent 2 hours coding Tetris for an interview. I lost to another candidate that completed 2 more features than I did in the same time period.
Super minor language nitpick, but I thought you might want to know. There are a couple places where you seem to have mixed up empathetic and emphatic. One section is titled “Emphethatic”. I’m not sure if you were trying to make a portmanteau or just misspelled it, but I was confused by it. Other than that, I appreciate you taking the time to write up something like this. Wish it existed when I interviewed in my younger days. (MS also asked me the manhole cover question.)
An inclusive interviewing process does not mean that you hire everyone. It means you reduce the weight of people's biases as part of identifying who you hire (because people turn out to be quite bad at prediction in hiring).
Sure, but if you are lucky enough to have an entire team of interviewers who have this much experience, you're probably not having the same hiring conversation that's happening in this thread.
- The companies that make an effort get a lot closer to population baselines than the ones that just give up.
- Organizational pressures are something leadership and management should be steering. I'd rather have hiring practices be an explicit choice than something that "just happens"
If the % of woman developers is 10% and management creates hiring goal of 50% it detorts reality. It means hr has to work harder at filling those female roles which often reduce their checkboxes while increasing the checkboxes for everyone else. Now you have to leaving positions unfilled longer in hopes of finding a candidate who matches a gender. You've turned the hiring process into a broken mess and require 1000 times more candidates.
Let's say you are successful. Let's say a class of companies are successful at this strategy. Lets use the example of faangs which are desirable places in terms of salary/brand. If faangs were successful at this that would reduce the % of female developers in other industry and assuming faangs are taking the best candidates that leaves the worst ones. Which then creates this reality where male programmers outclass female developers in these other industries. That makes it harder for women in general and makes this false impression that females are not as good as males.
To help women you really need to treat them equally. Trying to reach a goal of unhealthy unnatural % industry wide means women will left holding the bag when the music stops.
ipaddr is right that he described the actual situation with FAANGs scooping up all of high caliber underrepresented minority candidates (think black/women ivy league comp sci grads with high GPA).
But this also creates a positive feedback loop when more and more women decide to switch industries and pursue IT/Engineering jobs via bootcamps, college degrees, etc. I noticed the number of female candidates in UX/UI, fullstack, QA, Data Analytics - has increased in last several years.
Partly because the demand is still high for these professionals, partly because there is entire cottage industry of bootcamps churning out IT specialists en masse, partly these diversity hiring practices that opened up doors for women
Regardless of whether you're coming from educational elitism, you're still making sweeping claims about big groups of people based on extremely limited evidence.
I'm a bootcamp grad, and would not have gotten into the field if bootcamps did not exist. I'm about four years into my career now, currently working at a major well-reputed tech company, and haven't gotten an average-or-below annual performance review yet. (And one reason for that is that I tend to be cautious, critical, and thoughtful in my technical decisions.) There are a number of other people from my bootcamp class with similar results.
I am making a generalisation, based on having interviewed over 200 developers in the past 2 years as part of technical screening.
80%+ of the bootcampers were rubbish and shocked to be told their knowledge was way below where they thought it was.
A classic is a 6 week JavaScript bootcamp grad claiming to be an "expert in JavaScript" (their words) and couldn't explain the JS type system or basics of variable scope. That was the norm. That kind of rubbish.
I'm happy you're an exception and everyone gets a fair chance with me, regardless of background, but I am never shocked when I have to bin yet another bootcampers CV
"Everyone gets a fair chance with me, regardless of background" is an _extremely_ different statement than "anyone with an ounce of technical hiring ability avoids those bootcampers like wildfire".
If you mean "in my experience, bootcampers fail technical screens at much higher rates", then say that, instead of implying that you're stupid if you even consider hiring someone who went to a bootcamp.
if your goal is 50% women then you have to lower standards to achieve that.
You don't have to. But you'd remove them from the job market, making the pool smaller for other companies. IOW, a few companies can target 50% women, but that'll make it that much harder for other companies.
Thinking of it in terms of race might indicate more about how you view things. As an example, think about how frequently throughout history people in power have claimed that women "can't handle" the positions of power that men had. They cite all kinds of nonsense like "emotional" or "hysterical"... conveniently ignoring all of the hysterical and emotional men throughout history.
Think about how something like that would affect how companies are formed. Things seem much better now, but I merely wanted to highlight one of many kinds of biases that are actively affecting our society, even if they are hard to qualify.
Inclusive hiring practices, in my experience, strive to have a diverse funnel whereby under-represented groups get to be in consideration, but you still hire the best out of the pool. It may take longer to fill that pool, but many agree that it is worth it.
You can exclude mediocrity while also being exclusionary on other axes.
They are unrelated issues. In fact, I’ve even heard of exceptional people being abused/bullied for belonging to the wrong group to the point of being told “you couldn’t have done that” which itself is an assertion of their supposed mediocrity for exclusionary reasons.
Don’t assume you need to be bigoted to exclude mediocrity. Discriminating, yes, but not discriminatory against groups that inclusive hiring policies attempt to protect.
This take assumes a priori that inclusive hiring results in mediocrity. Sounds more like a reflection of biases, to be honest. Inclusive hiring means expanding your search criteria beyond "hire those that look like me, speak like me, have awesome education like me, and are basically smart like me". It turns out there are plenty of exceptional people outside of that narrow band.
> have awesome education like me, and are basically smart like me
At least this is meritocracy, the kind of thing that people (e.g. eugenicists) can make a serious argument for.
> look like me, speak like me
...is something that can't be justified except by terrible people. Even worse is "likes the same music and movies that I do" or "we coincidentally have mutual friends."
> Project 100,000 soldiers included those unable to speak English, those who had low mental aptitude or minor physical impairments, and those who were slightly over- or underweight.
You are moving the goalpost from mediocrity to disability.
We are a small Health Tech / AI automation start-up growing 3x YoY (we just raised our Series A round!) and looking to expand our platform team.
Our core platform consists of a front-end app, back-end API, SDK, and some DevEx tooling. The tech stack consists of AWS, Typescript, NextJS, React, Python, and the Serverless Framework.
We are looking for individuals with experience working as founding engineers in early-stage startups. The ideal candidate should be excited about learning new things, passionate about DevEx/DevProd, and comfortable cutting through ambiguity.
If that sounds exciting to you, apply on our website (we review every submission): https://www.thoughtful.ai/job?gh_jid=4354328005
I'm the HM for this role. If you want to learn a bit more about me, you can go to https://jes.al/