Tiamiyu Saheed Oluwatosin

- Lead and mentor a high-performing team of 10 engineers, fostering a culture of collaboration and growth through performance reviews and development plans.

- Oversee technical decisions to ensure code quality, scalability, and adherence to best practices across all engineering teams.

- Developed automated test setup and automation testing strategies to ensure high-quality, efficient testing processes that enhance product stability and reduce manual effort.

- Architected and reviewed Java/Spring Boot microservices with focus on concurrency, resource management, performance, reliability, and maintainability.

- Managed AWS and EKS-based delivery using Kubernetes, HPA, Argo CD, Helm, Docker, CI/CD, and operational tooling.

- Established observability and performance-testing practices using Prometheus, Grafana, OpenTelemetry, CloudWatch, Sentry, and JMeter.

- Implemented secure engineering and VAPT processes, including secure coding, authorization controls, credential handling, and software data privacy practices.

- Directed technical strategy, architecture, automated testing, DevOps process setup, resource planning, vendor evaluation, and cross-functional delivery.

- Work closely with departments like Product, Marketing, and IT to ensure technical alignment with business objectives & act as the technical liaison.

- Software Data Compliance: Ensure compliance with data regulations, software security, and data privacy.

- Manage budgets to optimize resource allocation, balancing team growth, infrastructure, and external tools procurement. Performance reviews and development plans.

Tech stack: Java, Spring Boot, AWS, EKS, ECS, Kubernetes, HPA, Argo CD, Helm, JavaScript, Node.js, React, Redux, MySQL, Kafka, RabbitMQ, CloudWatch, Sentry, RDS, Lambda, S3, Jenkins, Ansible, Azure DevOps, SonarQube, Prometheus, Grafana, OpenTelemetry, JMeter.

- Built a B2C E-commerce trading platform on Commercetools (headless backend engine)

- Commercetools Connect and Stripe payment integration

- Stripe Payment Element, SetupIntents, PaymentIntents, U.S. bank-account &Canadian PAD payment & webhooks

- ERP fulfillment workflows, Idempotency, retries, repair-on-read, and payment-state reconciliation

- Idempotency, retries, repair-on-read, and payment-state reconciliation

- Perform secure engineering practices like authorization, credential handling, JWT security, webhook signature validation, secret isolation, and PII-safe logging

- GitHub Actions, Jest, deployment, and observability

- Review and rigorously test commerce architecture covering product catalogs, pricing, customer segmentation, order management, API extensions, and subscription patterns.

- Worked with U.S. data and payment-compliance systems for a Chicago-based marketing firm, managing data handling, payment workflows, access controls, implementation decisions, and architecture.

- Define scalable data models and environment strategies that support multi-region and multi-brand expansion without unnecessary rework or technical debt.

- Advise on headless frontend integration, Storefront APIs, cart and checkout flows, session management, and payment integrations such as Stripe.

- Contribute to Java/Spring Boot and distributed-platform engineering using Kubernetes, HPA, Argo CD, Helm, AWS SQS, worker patterns, retries, DLQs, and distributed locking.

- Develop an agentic AI-accelerated development pipeline and document architecture decisions, patterns, trade-offs, and implementation guidance.

**Tech skills:** JavaScript, TypeScript, Python, Vite, Fastify, C#, AWS, Google Cloud Platform, Kubernetes, HPA, Argo CD, Helm, Docker, Kafka, RabbitMQ, SQS, .NET, Stripe, Nginx, MongoDB, SQL Server, Oracle, Terraform, Jenkins, Ansible, SonarQube.

I take on a challenging research role in leveraging Machine Learning to Enhance Big Data Usage.

* Algorithm Development: Design, implement, and optimize AI/ML algorithms for various research projects.

* Data Analysis: Collect, preprocess, and analyze large datasets to extract meaningful insights.

* Model Training: Train and fine-tune machine learning models using state-of-the-art techniques.

* Experimentation: Conduct experiments to validate hypotheses and improve model performance.

* Collaboration: Work closely with faculty, researchers, and other team members on interdisciplinary projects.

* Course Support: Assist in the preparation and delivery of lectures, labs, and workshops on AI/ML topics.

* Participated in the full software development lifecycle for research and financial-services use cases, including requirements, architecture, development, testing, deployment, and documentation.

* Developed Java/Spring Boot services and distributed processing workflows using AWS SQS, asynchronous workers, retries, DLQs, and distributed locking patterns.

* Used Mapbox and GeoJSON for map-based application features and large-data workflows, with attention to browser-side data handling and rendering performance.

* Conducted observability and performance testing using Prometheus, Grafana, OpenTelemetry, and JMeter to identify bottlenecks and validate service behavior.

* Led research teams in selecting, tuning, evaluating, and documenting AI/ML models; contributed to trustworthy AI research focused on LLM security, privacy, confidentiality, and poisoning attacks in RAG agents.

* Supported workshops, seminars, graduate research, technical reports, presentations, and AI/ML teaching activities.

* Student Mentorship: Provide guidance and support to students working on AI/ML projects.

* Grading: Evaluate assignments, exams, and projects, providing constructive feedback to students.