3+ years designing, deploying, and securing cloud infrastructure in regulated environments. I turn complex infrastructure problems into elegant, automated, security-first solutions.
Kehinde Afolarin Oyekunle — a DevOps & Site Reliability Engineer who started as a Youth Corper walking into a Data Centre in Lagos with nothing but curiosity and a hunger to learn.
3+ years later, I had built production systems from scratch, passed ISO audits, automated infrastructure, deployed applications used by entire organisations daily, and led a team of 6 engineers.
Now based in Middlesbrough, UK, I'm pursuing an MSc in Cybersecurity at Teesside University — exploring the intersection of AI and Cybersecurity as my research focus. I believe the engineers who will define the next decade build with security as the foundation, not an afterthought.
I'm actively seeking remote DevOps, SRE, or Cloud Infrastructure opportunities with global companies.
OOU ICT · 2020–2022
FOUNDATIONCoils Tech · 2022
GLOBAL EXPOSURECloud Exchange · 2022–2025
3 YEAR GROWTHFringe Infrastructure · 2025–2026
VMS · SECURE FILE SHARETeesside University · May 2026
ENROLLED · AI RESEARCHEnd-to-end automated web application built from concept to production. Eliminated all paper-based manual processes. Automated registration, approval workflows, and notifications. Includes full Disaster Recovery strategy.
Internal secure file sharing system built within a regulated data centre. Designed with security at its core — every file transfer meets ISO and PCI DSS standards. Zero tolerance for compliance gaps.
Full real-time observability using Prometheus and Grafana for EC2 and database performance. Custom alerting to detect anomalies before they become incidents. Zero SLA breaches during tenure.
Automated full AWS environment provisioning with Terraform and CloudFormation. Cut setup time by 50%. Includes VPC, IAM least-privilege, security groups, backup automation and DR runbooks.
My MSc research sits at the intersection of two of the most critical fields in modern technology — Cybersecurity and Artificial Intelligence. I believe AI is rapidly becoming both the most powerful tool in a security engineer's arsenal and the most dangerous new attack surface.
My goal is to explore how AI-powered threat detection, anomaly identification, and automated incident response can make infrastructure inherently more secure — not just at the perimeter, but from within every layer of the stack.
Research Direction: Investigating the application of machine learning models for real-time detection of anomalous infrastructure behaviour in cloud environments — building on my hands-on experience with Prometheus, Grafana, and AWS CloudWatch observability stacks to design AI-augmented monitoring systems that reduce mean time to detect (MTTD) and mean time to respond (MTTR) to security incidents.