Favour Ezeugwa has built her career across cloud computing, cybersecurity and artificial intelligence, combining industry experience with research into the performance and security of modern digital systems.

A Solutions Architect at Amazon Web Services (AWS), Ezeugwa works with organizations on cloud architecture, with experience in identity and access management, encryption, network security, monitoring and artificial intelligence.

Her route into technology was unconventional. After earning a bachelor’s degree in geology from Nnamdi Azikiwe University in Nigeria, she moved into software development, completing more than 1,300 hours of full-stack development training through Microverse. She later reviewed hundreds of code submissions from other developers before pursuing graduate studies in computer information systems.

At Prairie View A&M University in Texas, Ezeugwa earned a Master of Science in Computer Information Systems with a 4.0 GPA. While completing the programme, she developed an AI-powered chatbot for the university’s College of Engineering using Amazon Q Business and published research on cloud infrastructure, cybersecurity and emerging technologies.

Testing a different approach to cloud computing

In July 2024, Ezeugwa published her independent research on how edge computing and serverless architecture could improve the performance, cost and sustainability of cloud-based big data systems.

Using a simulated smart-city environment, she compared the approach with a traditional cloud architecture.

The results showed peak-hour latency falling from 149.73 milliseconds to 88.94 milliseconds. Operational costs dropped by about 30 per cent, while throughput increased by 50 per cent. The study also reported lower energy consumption and carbon emissions.

The findings showed how processing data closer to where it is generated, combined with serverless computing, could improve the efficiency of large, time-sensitive workloads.

Examining cybersecurity threats*

Ezeugwa’s research also extended into cybersecurity.

In a collaborative study on ransomware and botnet attacks affecting remote workforces, she and other researchers evaluated a layered security approach combining multi-factor authentication, endpoint detection and response, encryption, network segmentation and Zero Trust principles.

In one simulated departmental scenario, the approach achieved a five-minute response time and 95 per cent containment efficiency. The research also found that network segmentation could restrict an attacker’s lateral movement after an initial compromise.

Another study examined the security-performance trade-offs in Internet of Things networks supporting AI-driven home appliances. The researchers found that stronger encryption and authentication increased latency and computational demand, highlighting the challenge of strengthening security without significantly affecting system performance.

They proposed an adaptive framework that could adjust security controls according to changing threat conditions and operational requirements.

From research to cloud architecture

In 2024, Ezeugwa joined AWS as a Solutions Architect Intern, where she worked on a generative AI application using Amazon Bedrock Knowledge Bases and retrieval-augmented generation.

The application connected generative AI with stored organizational information, supported by AWS services for document storage, authentication, application logic and data management.

After completing her master’s degree, Ezeugwa joined AWS full time as a Solutions Architect in January 2025.

Her work involves helping organizations design cloud architectures around requirements including security, scalability and resilience.

As artificial intelligence becomes more connected to enterprise data and systems, Ezeugwa has also focused on the security questions that come with that access.

“When AI systems start accessing company data and interacting with other systems, access becomes very important,” Ezeugwa said. “You have to think carefully about what the system should be allowed to do and what it shouldn’t.”

Contributing through research and technical review

Ezeugwa’s involvement in research has also extended to peer review.

In 2024, she was invited by the Asian Journal of Research in Computer Science to review research involving robotics and artificial intelligence in healthcare. By November 2025, she had also begun serving as a peer reviewer for IEEE Access, contributing to the evaluation of research submitted to the multidisciplinary journal.

She has also shared practical applications of artificial intelligence through AWS. In an AWS Training and Certification blog post, Ezeugwa demonstrated how Anthropic’s Claude models in Amazon Bedrock could be used to build a personalised AWS certification coach.

The post showed how generative AI could be applied to technical learning through an interactive system tailored to certification preparation.

A growing focus on cloud security and AI

Ezeugwa’s work now increasingly brings together cloud security and artificial intelligence.

As organizations give AI systems greater access to company information, APIs and other digital resources, she is interested in how those systems can be secured without limiting their usefulness. She is also exploring how artificial intelligence can help security teams identify risks and respond to threats across complex cloud environments.

“I look at it from both directions,” Ezeugwa said. “How do we secure AI systems as they become more capable, and how can we use AI to improve security?”

That combination of cloud architecture, cybersecurity research and practical AI work is shaping the direction of Ezeugwa’s career as she continues to work on the security challenges emerging alongside increasingly capable cloud and AI systems.