01
Software Systems
Production Python services, API architecture, data workflows, automated testing, and reliability engineering.
Backend · AI infrastructure · Platform engineering
Production backends, AI infrastructure, and cloud platforms.
I’m Godson David, an engineer with 6 years designing and shipping systems across fintech, SaaS, and AI tooling. I specialise in Python/Django backends, AWS and Azure deployments, Kubernetes and Terraform delivery, and LLM-integrated pipelines.
- 200+AI benchmark submissions evaluated
- 85%+reduction in deployment failures
- 99.5%+availability across distributed backends
01 / ENGINEERING FOCUS
Engineering across the stack.
From the service boundary to production operations, I approach software as a complete system—not a collection of disconnected features.
02
Cloud & Platform
AWS and Azure infrastructure, Kubernetes orchestration, Terraform, CI/CD, observability, and deployment operations.
03
AI Infrastructure
LLM evaluation pipelines, RAG systems, agentic workflows, benchmark harnesses, and production model integrations.
04
Application Engineering
End-to-end SaaS and fintech products, React interfaces, backend integrations, and accessible responsive experiences.
02 / SELECTED WORK
Evidence over adjectives.
Production engineering work spanning model evaluation, deployment reliability, backend performance, and full-stack product delivery.
Evaluation infrastructure for frontier coding models.
Designed automated SWE-style evaluation pipelines that processed more than 200 model submissions across five task categories. Built 35+ structured tasks and test harnesses covering reasoning, instruction adherence, and cross-codebase bug detection.
- 200+
- model submissions
- 3
- frontier coding models
- 2–4h
- saved per benchmark
Release systems designed to fail less often.
Implemented CI/CD validation pipelines and automated test gates across five client projects. The work reduced deployment failure rates by more than 85%, cut manual QA effort by 60%, and enabled same-day releases on previously manual workflows.
- 85%+
- fewer failed deployments
- 60%
- less manual QA
- 99.5%+
- service availability restored
EARLIER PRODUCT BUILDS
Three selected applications
03 / EXPERIENCE
Production work across products and teams.
Six years spanning client delivery, backend product engineering, AI tooling, cloud operations, and technical leadership.
04 / TECHNICAL STACK
Tools selected for the system.
Technologies I use across service development, data, infrastructure, AI integration, and interfaces—grouped by purpose rather than proficiency scores.
05 / CREDENTIALS
Continuous technical development.
06 / START A CONVERSATION
Have a system to build?
I’m available for full-time remote backend, AI infrastructure, and platform engineering roles, as well as selected technical engagements.