Assessing Fit for Technology Staffing Projects
In today’s fast-moving tech landscape, certain IT skills are in exceptionally high demand—and screening candidates thoroughly for these skills is crucial.
TECHNOLOGY STAFFING
Shailesh Bokil
5/8/20251 min read
In today’s fast-moving tech landscape, certain IT skills are in exceptionally high demand—and screening candidates thoroughly for these skills is crucial to avoid costly mis-hires that can delay projects, compromise security, or impact product quality.
One key differentiator is that at Epic Talent Solutions, technical screenings are conducted by our exclusive network of experienced professionals that have worked at tech companies like Amazon, Meta, Microsoft, etc. which means that you get vetted candidates that will deliver.
Epic Talent Solutions uses Technical Screening Checklists tailored for evaluating high-demand IT talent:
Pre-Interview (Resume/Pre-Screen):
. Certifications or credentials relevant to claimed skill (e.g., AWS Certified Solutions Architect
. Projects or roles that clearly demonstrate applied expertise
. Clarity of role in team or deliverables (not just buzzwords)
. Evidence of upskilling or recent learning (courses, GitHub activity, blog posts)
Technical Screening Questions Examples:
Cloud Computing (e.g., AWS)
• Can they describe setting up a VPC, subnets, and security groups?
• Have they implemented cost optimization strategies (e.g., Reserved Instances, Spot Instances)?
• Can they explain CI/CD integration with AWS services?
Cybersecurity
• Do they know common vulnerabilities (OWASP Top 10)?
• Can they explain how to design a Zero Trust architecture?
• Experience with security tools like Splunk, CrowdStrike, or Qualys?
DevOps / Infrastructure as Code
• Hands-on experience with Terraform or CloudFormation?
• Can they describe setting up automated pipelines in Jenkins, GitHub Actions, etc.?
• Do they know containerization tools like Docker and orchestration via Kubernetes?
AI/ML / Data Science
• Can they explain a recent model they built or tuned?
• Familiar with tools like TensorFlow, PyTorch, or scikit-learn?
• Experience with MLOps or model deployment pipelines?
Post-Interview Evaluation
• Passed technical assessment?
• Soft skills: communication, adaptability, remote collaboration?
• Cultural fit with company and team’s pace, style, values?