Tag Archives: engineering hiring

Tech Resumes Today and Tomorrow

Almost anyone who works for a living has a resume and maintains it with some effort. Due to the private nature and changeability of resume content, most people author their own resumes. Whether a resume is diligently adorned from time to time or reluctantly updated only to follow the social norm, it tells a lot about its author – often more than what the author intends to.

While it’s fine to borrow layout or even writing styles from others, the content of your resume would better be your own work. Your resume represents so much about your accumulated skills and professional accomplishment over some of your most productive years that it’s justifiably worth some real effort of your own to assemble it. More importantly you’re going to back the words written on your resume during the job interviews and it’s easier to back your own words than others. However, before you finalize the “production version” of your resume it’s a good idea to solicit feedback from your trusted friends and refine it as you see fit.

Resume screening and deep-dive

In the software talent acquisition process, resume review is one of the most boring but important tasks. Getting the most out of a bunch of word streams of various writing styles certainly demands effort, and the ongoing fierce competition for software talent especially in the Silicon Valley helps ensure it’s a lengthy, if not endless, effort.

Generally there is a process in which the recruiter screens quantity resumes to filter out the obvious unmatched, and another process involving a deep dive into the stream of words to try to compose, however superficially it might be, a virtual representative of the resume owner. Resume screening happens upfront and word stream diving happens typically after the initial scans, phone or early round interviews.

During resume screening, usually only technical keywords relevant to the very job opening and a rough sense of current career state and professional seniority will be extracted in a cursory fashion. The Professional Summary section weighs a lot in this process as each resume only gets a sub-minute glance window due to volume. The more in-depth resume evaluation involves digging into the individual jobs listed in the resume. Besides the information intentionally conveyed by the author to the audience, the reviewer might also try to read between the lines to deduce what expertise the job candidate might actually possess. Whether the evaluation process is implicit or well defined, a good chunk of the following will be compiled in some way:

  • Current and most recent job positions/ranks/responsibilities
  • Has the candidate been with highly regarded companies in recent years?
  • Total years of professional experience at the sought level
  • Is the candidate still playing a hands-on role?
  • Candidate’s academic major and highest degree attained
  • Did the candidate graduate from a reputable or preferably Ivy League school?
  • Does the candidate have a progressive career history?
  • Average duration of individual jobs in the past

A capable technical recruiter can help carry out quality resume screening work and perhaps part of the in-depth evaluation for the hiring manager. But even with a well-prepared reader’s digest provided by the recruiter, the hiring manager ultimately has to dedicate his/her own bandwidth to at least read through the resume which is supposedly the source of data directly from the candidate.

Polished vs Crude

Software engineers generally are not the best marketers. I’ve seen many resumes littered with numerous boldfaced keywords throughout the content resulting in a blob of randomly cluttered text. Sadly, often times the cluttering decoration is actually the work by head-hunters who try to impress the hiring managers with job matching keywords. Some resumes are downright fraudulent work. The worst ones show clear evidence of poorly automated fabrication of clause-matching skillsets to the specific job post.

A resume modestly revealing exceptional technical expertise in simple concise writing style often gets the highest respect. Hard-core software veterans tend to project an image of raw, no-non-sense personality, often along with a dose of attitude. Many would prefer to keep their resumes less well-packaged even if they’re capable of being so. Most of the time that dose of attitude is just a reflection of high confidence. However, sometimes an excessively righteous tone, for instance, can be an indication of a narcissistic non-team player. Whether that dose of attitude is healthy or excessive, one will surely find out during the in-person interviews.

The hiring ecosystem

I think the entire hiring ecosystem today is very inefficient. You have job seekers wanting to trade their skills for the best available compensation package, and employers offering market-rate compensation in exchange for the skills. Both parties claim to be some of the best themselves, but neither of them trusts each other. Recruiters, head-hunters aren’t the unbiased middleman because they work one-sidedly for the employers who pay them and filling the job openings ASAP is their only priority, instead of finding the best match. Job boards also operate favorably for the employers who fund their revenue. Same for professional social networking sites such as LinkedIn whose main revenue comes from selling analytics data to companies.

Such one-sidedness is not necessarily a problem. In trading, you also have many brokers playing a one-sided middleman role. But typical products being traded have well-defined specifications and/or pricing standards within the product space. In hiring, you’re trading intangible skills. There is no common specifications or standards for skills that both the employers and job seekers can use as references.

Theoretically, trading your skills for compensation should be a fair game, but in reality, unless you possess certain skills that are in high demand at the time, employers usually have the upper hand perhaps because a majority of workers are perceived replaceable commodity. And evidently, even high-demand skills change from time to time. Unfortunately I don’t see how this one-sidedness will change in the foreseeable future.

The future of tech resumes

Today, composing a resume is largely, if not wholly, a marketing exercise. Had there been a set of common specifications of skills, assembling a resume would be more like an accounting exercise in which skills and experience are being logged in accordance with some standard weighing matrix. Resumes would then be a much more objective source for qualification data. Without some sort of skill measuring standard, employers will continue to come up with their wishful job requirement and job seekers will keep assembling their resumes in their own writing styles and with subjectively rated skill levels. As a result, skill match between a given job post and a resume is almost always superficial or accidental.

What is a practical rating method for skills is the million-dollar question here. Peeping into the not-too-far future, I suspect there is going to be some standard-based semantic foundation on top of which job history and academic achievement can be systematically rated. In addition to that, perhaps some credential scoring systems similar to StackOverflow.com’s model can also be used in the rating methodology.

All that would require an underlying layer of some sort of standard software engineering ontology (e.g. “ISO/IEC/IEEE 24765: Systems and Software Engineering Vocabulary”) so that all the job functions and skillsets logged in a resume have referential meanings. The raw content of a resume would be composed in a format suitable for machine interpretation (e.g. Resource Description Framework a.k.a. RDF, Semantic Web). As to the presentation-layer tools, some readily available reader or browser would allow a human to interactively query the latest information in any area of interest within a resume in various levels of granularity and perform ad-hoc analysis and qualification comparison among competing candidates. Job posts would also be structuralized in accordance with the same underlying semantics, making matching job seekers with employers more of science than art.

The War For Software Talent

Having built software engineering teams for startups throughout my recent career, I must say that it’s not the easiest thing to do. It has gotten even tougher in the past few years as competition for software veterans has been more fierce than ever.

A mundane supply-and-demand issue

Prominent technology companies such as Google, Twitter, Amazon, have evolved over the past decade to become powerful titans by all standards. They have been vacuuming the talent space like black holes. Their continual sky-high stock value has led to spin-offs of child startups by their departed alumni who are often times some of the best talents themselves. These spun-off entrepreneurs were once key contributors but are no longer so, thus depleting the talent pool for hire.

The spin-offs leave the mother companies no choice but to step up their vacuum machine power. Meanwhile, these spun-offs create their own vacuum machines and, with some elite company names in their profiles, instantly become additional black holes to scoop up talents. That’s all good in helping to prosper the technology industry. But it inconveniently starves the average startups of desperately needed veterans, and running the code below is not going to help.

Because of the imbalance in the supply-and-demand of top talents, the compensation package for them has skyrocketed to the point that the average startups are having a hard time to justify it. Unlike established and well-funded companies, these startups must watch where every single dime goes and a salary at the level of a small startup CEO’s range for a veteran engineer can be a deal breaker.

Product Managers, QA, DevOps, …

For any given software engineering team, focus is often put on the engineers responsible for the very coding task. But any company who has ever built real-world products realizes how tough it would be to deliver them without an able product manager. Star product managers with adequate technical background and product management skills are equally hard to find. In all my previous startup ventures, product managers have always been some of the hardest roles to fill with the right people.

Good QA engineers are more difficult to find than R&D engineers. Many engineers simply lack the attributes, including patience and a detective mind, required to perform well in quality assurance. In addition, most people with strong programming skills prefer seeking R&D jobs to QA jobs. The end result is that many QA engineers come from a background of less stringent training in programming. In a technology demanding engineering team, that can be a barrier to carrying out quality QA tasks.

Experienced operations staff who handle systems and database administration have always been hard to find. The fact that I’ve been forced to play those roles myself on and off since my first startup venture in the 90′s tells a lot. With more and more cloud-based services arising and blurring the line between the software development and network operations worlds, DevOps were born. Instead of supporting non-technical users, they support highly technical software engineers. So, now we’re talking about a hard-to-find sys op with some software engineering background. These DevOps are like network engineers in the old days. They are endangered species.

What about quants?

The recent Big Data analytics movement has spiked a sudden demand of data scientists, a.k.a. quants. Quants possess domain expertise in quantitative, statistical analysis and machine learning algorithms that are crucial to businesses that need to digest their ever growing Big Data. Often times, an advanced degree in a natural science discipline such as physics or mathematics is required to qualify for such jobs, although other disciplines like mechanical engineering, operations research also prove highly applicable.

Despite the demanding requirement, I was having less trouble finding qualified quants than veteran software engineers. Perhaps demand for quants is still relatively fresh and not many companies know how best to tackle it yet. Coming from a natural science academic background myself, it was also a bit troubling to find out that a quant with a PhD in Physics from MIT and 5 years of post-Doctoral work costs less than a software engineer with a BS in Computer Science from an average college and 5 years of programming experience.

Where can I find them?

To build or grow your engineering team, if you do not already have at least a couple of trusted lieutenants and engineers as part of the team’s backbone, you will surely be up against a pretty big challenge. Unfortunately, that’s not an uncommon situation. As you’re advancing your career throughout the years, those who were once your star team members might’ve grown to playing similar role to yours or starting their own ventures (and competing with you for talents). So, chances are that there are some critical roles you need to fill from time to time.

Conventional wisdom suggests that hiring through internal referrals is always preferred. That is still true, as ever. It also makes sense to expand it further to connect with your friends, alumni, excolleagues, advisory board and board of directors for more leads. While it’s hard to guarantee success, posting jobs on job boards and professional social networks such as Monster and LinkedIn remains logical steps to advertise your hiring needs. One can also try local community networks like Craigslist especially if you only want local candidates.

For projects with well-defined specs and clear metric for measuring success, using less expensive off-shore resources may make sense. Cost for a near-shore full-time engineer is between one-third and half of that of a local engineer, but one should factor in the extra management cost incurred. Near-shore has an advantage of more synchronous time zones. Trusted references about their service quality are essential in your evaluation process.

As for quants, there might not be many candidates available for hiring through the above channels. Because academic specialty weighs a lot in a quant job’s requirement, it makes sense to try acquire those talents directly from the academia. NACELink (http://www.nacelink.com/) is a great starting point for advertising your need through their extensive school network.


If you foresee an on-going hiring need, you should get help from technical recruiters. They work on a contingency or retained basis. The latter is often preferred when you have a relatively large number of job openings to be filled in the short term. It’s recommended that a goal with a timeline be set upfront to measure success so as to keep precious time and budget in control. On the other hand, there is no reason for you to limit your hiring channel to only one type of recruiters.

Finding competent technical recruiters is tricky, as you wouldn’t know whether a recruiter is good or not till you have the chance to at least go through a couple of leads from him/her. For each job opening, it’s recommended that you always provide your recruiters a carefully thought-out set of technical questions for them to go over as the initial filter. A couple of reasons for that:

1. Nobody knows better than yourself what exactly the expertise you want from the candidate
2. Many technical recruiters don’t necessarily have strong technical background, despite their technical title

Conclusion: No magic pills

Finding top talents to join your engineering team can be an exhausting effort, fruitless at times. You have to invest a huge amount of your own time and effort, even if you use recruiters. The fact is that there are great techies who aren’t good at marketing themselves and mediocre ones with excellent profiles on paper. People talk about the 80-20 rule, but you’ll be considered very lucky if 20% of your team are truly top talents.

A significant part in the process of acquiring talents involves some selling effort. While selling the company’s prospect and evangelizing the adopted technologies help, many engineering veterans nowadays are sophisticated enough to have done their homework. So, the key is not to oversell them and be consistent among the “sellers”. It’s kind of analogous to reporting to your investors in a board meeting – just highlight the key achievements that count and back them by unambiguous metrics. They already did their homework. Even if not, you should assume they did.