Building winning a team for Workhuman

Introduction & Context

Workhuman is a multinational company who focuses on social recognition; their product allows employees to recognise and reward each other.

With the launch of their new Workhuman iQ platform, which utilises AI to provide insights on skills, performance etc., they needed to build out a team to make sure that they delivered on time.

Challenges

While Workhuman themselves are considered one of the best employers in Ireland, it didn’t mean that they were without challenges when hiring for this team. A number of factors came into play, with first and foremost being the availability of the required talent in the location they needed.

With any new team, there is generally a preference for them to grow and collaborate in person. While this itself isn’t necessarily a challenge, it was the niche skill requirements which made hiring for these roles that bit more tricky.

Given the critical nature of this team, Workhuman were committed to hiring the right people. This meant daily collaboration between our teams, continuous feedback on CVs, interviews and very transparent communication overall. While we could work very well together, there were some limitations.

Availability of Talent

As there isn’t a huge number of professionals within the AI space (as it’s a relatively new area in recent years) it meant two things - a small number of Workhumans needed to conduct a large number of interviews - on top of their day to day work of trying to meet the project deadline - and working through what were realistic expectations when it came to suitable candidates.

This was a prime example of partnership communication - we leaned on each other to help move things forward. While we were able to give market insights to Workhuman, around the availability of talent, where they are located, what other opportunities they were looking at, salary expectations etc, we relied completely on them to take this information on board and make adjustments where needed. In turn, when they gave approval for any changes it was our responsibility to take that to market.

The limited interview team created bottlenecks, but nothing that couldn’t be worked through. Once we identified the issue, which was predominately more CVs being sent than the hiring managers could review with a quick turnaround, the solution was to further refine the role requirements to reduce the number of CVs being sent.

Remote, Hybrid & RTO

Workhuman are hybrid first, and going into the partnership this expectation was set. What we found was that a significant number of people relocated away from Dublin during Covid, which made it more challenging to get candidates who were at senior levels of experience in particular. We also discovered that, for candidates, the desire to remain predominantly remote is still there. Most folk seem to be open to office visits every now and then, but the preference is still very much mostly remote.

Challenges within our team

Within our team, the roles were allocated per vertical so that each received equal attention. Each position had their own challenges:

A major challenge for the backend role was that anyone who had the hands-on GenAI exp, at a very senior/IC level, was either a Data Scientist or ML Engineer. The problem was, if they had the programming experience, it was perhaps at the early stages of their career - like a stepping stone before transitioning into the Data Science space and they wouldn't have done enough coding. Similarly on the flipside; there were great individual contributor Python engineers who had worked in AI environments, but didn't have extensive, hands-on experience with AI-related tools as these responsibilities were fulfilled by Data or AI/ML teams.. The eventual hire was UK-based.

One of the biggest hurdles we faced was finding candidates with the right production-grade experience, especially given how niche the talent pool was. That said, the work itself really resonated with people, and many candidates were genuinely excited about the opportunity, which made conversations much easier.

When it came to the senior roles, we did get some feedback from candidates that the job spec felt a bit overwhelming. Once we worked together to narrow down the key priorities, things really fell into place, and we were able to move forward more smoothly.

Another thing we noticed was how much of a difference it makes when interview schedules and panel availability are locked in early. It speeds things up and keeps the momentum going, which is so important when you're trying to secure top talent.

Initially, for the GenAI and MLOps Engineer positions, the hiring process focused on candidates with a blend of Machine Learning, Generative AI, and DevOps expertise, which proved to be a niche and challenging profile to source. After a few months, the focus shifted to a more Site Reliability Engineering (SRE)-oriented profile, following internal discussions and realignment on the role requirements.

During this transition, we worked closely with the team to ensure alignment between stakeholders and clarity on the ideal candidate profile. Once this clarity was established, we successfully filled the role within three weeks, delivering a highly qualified candidate who matched the refined requirements.

The main challenge with the Engineering Manager position was dealing with a very shallow pool of candidates. GenAI is a particularly new technical domain and Ireland is still in its infancy when adopting GenAI in general. The people who were brought into companies to scale up their GenAI components were often outside consultants, very few GenAI SMEs were in-house with many companies, and if they were they were on top of the food chain in terms of salary etc.

The AI Architect was a particularly tricky role. Many candidates had relevant experience, but Workhuman needed someone who could architect AI systems for use across the company, not just experience working with customer solutions, and they also had to be familiar with AI ethics and whitepapers etc. and helping evangelise AI internally.

Solution

Quite often, with new teams, role requirements can evolve throughout the hiring process. We found this to be the case with Workhuman; as folk were interviewing we were able to determine what were the absolute must-haves for each position. This needed to be considered in relation to skills needed to do the role but also what was learnable (and was there someone on the team who could offer that learning).

Execution

To ensure the success of the project, we needed to be very intentional in our process. We followed our standard process, and amplified where needed.

Our first stop is always a briefing call. We spoke directly to the hiring managers of each position to understand the day to day responsibilities, the “must have” experience as well as what kind of personality would best suit the roles.

It also meant a quick turnaround time for feedback on CVs and interviews, which given that the majority of people who interview for a new position are in multiple processes, was critical.

What was integral to the success of these positions was having daily contact with hiring managers, as it meant we could discuss feedback from candidates, any market findings and also any sticking points of finding the right people.

Outcome

While it took longer than anticipated, with learnings on both sides, we successfully completed hiring Workhuman’s first AI team. One of the biggest factors for success was strong communication between us. When we shared market insights or candidate feedback, Workhuman were able to make adjustments where necessary. Similarly, when Workhuman fed back to us that some profiles didn’t quite hit the brief, we were able to make changes quickly and re-centre our searches.

As this was a team.Build partnership, we included video marketing for Workhuman. The videos we shot included people from the team that candidates would be joining - they could hear directly from future colleagues about the project, challenges and some light hearted things too. Doing this type of marketing had a huge impact for Workhuman, as it allowed them to showcase their personal side immediately and give people a sense of what it’s like on the ground.

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