Training on Assessing Technical Skills in Interviews

Recruiting leaders in our community have wrestled with how to balance AI-enabled candidates. We worked with a team that's hiring a data analyst to develop an approach to assess for SQL skills. Here's how we structured the process to try to balance the very likely possibility of candidates using AI tools. First, making use of new tools has always been disruptive to recruiting and is the exciting part of moving our collective work forward. On the one hand, when you have someone join your team you want them to be resourceful and efficient. This is a really positive and great thing! On the other hand, you also want to make sure they understand how things work and use their individual creativity to think of new and novel solutions. Here's the process we're trying: Take-home assignment Data: we provided the database schema and sample set of data of typical recruiting data - jobs, applications, offers Questions: we asked a series of questions about the data for common use cases to test both recruiting intuition and hard skills. For example, calculating offer acceptance rates test for their intuition on anchoring to the appropriate date, handling candidates with multiple offers, and joining tables to get to a good answer. So yes, candidates can and will likely use some 'assistance' but AI responses are only as good as the prompt. Assuming the logic and explanation make sense, you can then dig deeper at onsite. Onsite interview Test their understanding by continuing to build upon the take-home assignment in a live interview. For example, pull up a candidate's response to calculating offer acceptance rates and ask them to adapt it to group by each department. If they didn't write it or understand their initial take-home response, it will be very evident in the live interview. However, someone that understood the result and just used AI to build it faster could demonstrate how to make the adjustments Curiosity - a characteristic of a high performing analyst is their level of curiosity. When given a dataset they can't help but explore it beyond the prompt. It's like an artist with paint and a canvas, the possibilities! So a great open question to assess for both curiosity and recruiting domain knowledge is to ask what other questions they have about the data, the process that drives the inputs, or other metrics that could be derived. What techniques are you trying to find a healthy balance to assess AI-enabled candidates?

🔥 How I Would Assess You in a Technical QA Interview (as an Interviewer!) 🔥 As a Software Engineer in Test, I’ve been on both sides of the interview process—preparing rigorously and evaluating candidates. If I were your interviewer, here’s how I’d assess your skills and what I’d expect from a top candidate. ✅ Do You Know the Fundamentals? I’d start by testing your understanding of SDLC, STLC, Agile (Scrum/Kanban) and different testing types (functional, regression, API, performance, security). Strong fundamentals = a strong candidate. 🖥 Can You Apply Your Knowledge? Theory is great, but can you write solid test cases, create a test plan, and log detailed bug reports? I’d ask you to demonstrate: • How you test an API using Postman/Swagger • How you validate data with SQL queries • How you analyze web traffic using DevTools, Fiddler, or Charles Proxy 🛠 How Comfortable Are You with Automation & Performance Testing? If the role requires automation, I’d expect you to have hands-on experience with: • Selenium, Cypress, Playwright (UI automation) • CI/CD tools like Jenkins, GitHub Actions, or GitLab CI/CD • Performance testing with JMeter or k6 📖 Can You Tackle Real-World QA Challenges? Expect scenario-based questions like: • How do you test an API from scratch? • What’s the difference between sanity and smoke testing? • How would you implement test automation in an Agile project? 🎯 How Well Do You Solve Problems & Work with a Team? I’d look for structured answers using the STAR method (Situation, Task, Action, Result) when you explain: • A time you found a critical bug before release • How you handled conflicting priorities • Your experience with collaborating with developers on fixing defects 💡 What Would Impress Me as an Interviewer? ✔️ You’ve researched the company and understand our tech stack ✔️ You communicate clearly and structure your answers well ✔️ You show enthusiasm and ask insightful questions ✔️ You’ve done mock interviews and come prepared with real examples 🚀 Want to stand out? Come prepared, be confident, and think like a QA leader! 👇 What’s the toughest QA interview question you’ve faced? Drop it in the comments! 💬 #QA #SoftwareTesting #TechnicalInterview #CareerGrowth #JobSearch #InterviewPreparation #QAInterview #TechInterview #JobInterview #MockInterview #InterviewTips #CareerSuccess #InterviewReady #Hiring #InterviewQuestions #AceTheInterview #InterviewSkills #JobHunt

I almost rejected one of the best JavaScript developers I've ever hired. During his first technical interview, Adam (not his real name) struggled with a whiteboard coding exercise. His solution was inefficient, and he seemed to miss obvious optimisations. Based on our standard process, he was a clear rejection. But something caught my attention—his problem-solving approach was unique. While his code wasn't optimal, his questions revealed a depth of understanding about edge cases and potential pitfalls that most candidates missed entirely. I broke protocol and scheduled a second interview with a different format: a pair programming session on a real (sanitised) problem from our codebase. The transformation was remarkable. Away from the artificial whiteboard environment, Adam flourished. He wrote clean, elegant code, communicated his thought process clearly, and even identified a bug in our existing solution. Adam went on to become one of the top performers, leading several critical projects and mentoring junior developers. This experience fundamentally changed how I help to prepare hiring managers for interviews: __I now review candidate resumes looking for evidence of both technical skills AND problem-solving approaches __I suggest to prepare multiple assessment formats to accommodate different working styles __I always recommend to bring another technical interviewer for a second perspective Has anyone else had a similar experience with a candidate who performed differently across different interview formats? What did you learn? #TechHiring #InterviewExcellence #CandidateExperience