James Muganzi

Python Backend Engineer with hands-on experience building production-grade APIs, asynchronous services, AI-enabled workflows, automation systems and data-intensive applications. Experienced with Python, FastAPI, PostgreSQL, Redis, pgvector, Celery, JWT/OAuth2, RBAC, automated testing and CI/CD. Built solutions involving semantic search, background processing, payment integrations, AI services and multi-channel notifications, with complementary React and Next.js experience.

Google IT Automation with Python Professional Certificate holder.

Researcher at CloudFactory (2025-11 – Present)

• Verify public-source information through 7 stages research, cross-checking and classification before converting findings into operational records.
• Process 50+ research records per work cycle, maintaining accuracy, consistency and source traceability.
• Cross-check 10 - 15 independent sources when information conflicts, resolving discrepancies before submitting records for review.
• Audit research records against 4 quality criteria: completeness, classification accuracy, evidence reliability and formatting consistency.
• Maintain source links, exception notes and verification evidence so reviewers can validate findings without repeating initial research.
• Submit verified records to distributed teams within project deadlines while protecting confidential data and following client guidelines.

Backend Developer at Blueprint AI (2024-08 – Present)

• Maintain Python/FastAPI services across 4 product workflows: authentication, business logic, data processing and frontend integration.
• Develop 20+ FastAPI endpoints using Pydantic, SQLAlchemy and PostgreSQL, standardizing validation and API response contracts.
• Expose Python machine-learning outputs through REST interfaces, enabling frontend features without direct dependencies on model code.
• Tune 3 database performance paths SQL queries, ORM operations and serialization to reduce redundant processing in backend services.
• Troubleshoot failures across 4 integration boundaries: APIs, PostgreSQL, authentication and external services; implement targeted fixes.
• Ship Python backend changes alongside React-facing features using Git-based collaboration and iterative releases.

Data Scientist / Backend Engineer at Blueprint AI (2023-12 – 2024-08)

• Built Python data workflows covering 5 stages: ingestion, preprocessing, feature engineering, training and evaluation.
• Transformed multi-source datasets with pandas and NumPy into consistent, model-ready inputs for client analytics work.
• Evaluated supervised scikit-learn models through iterative validation and feature refinement to strengthen predictive performance.
• Standardized recurring preprocessing steps cleaning, transformation and feature preparation into reusable Python pipelines.
• Presented model findings through Matplotlib and Seaborn reports, translating technical results into stakeholder-ready visuals.
• Supported deployments through 3 reliability practices: model validation, backend integration and production monitoring.

IT Automation Apprentice at Mentor Me Collective (2025-07 – 2026-01)

• Built 10+ Python scripts for repetitive IT tasks, replacing manual steps with consistent, repeatable execution.
• Automated categories of operational tasks file processing, input validation and CLI utilities using functions and exception handling.
• Converted multi-step manual procedures into reusable scripts, making recurring IT operations easier to rerun and troubleshoot.
• Collaborated through 3 Git/GitHub practices: branching, pull requests and tracked revisions across remote assignments.
• Prototyped cloud-aware automation and infrastructure checks to assist with technical troubleshooting and operational support.
• Diagnosed Python script failures using debugging, configuration management and version-controlled fixes.

AI & Machine Learning Trainee at Power Learn Project (2024-06 – 2024-09)

• Produced a climate-risk prototype covering 4 decision areas: drought, flooding, food insecurity and crop yields.
• Prepared environmental datasets through 3 steps cleaning, transformation and feature exploration—using Python, pandas and NumPy.
• Analyzed climate-risk data using supervised machine-learning and statistical methods, converting model output into decision-support insights.
• Translated natural-language questions into analytical queries so non-technical users could explore climate-risk findings.
• Unified 15 elements environmental datasets, model predictions and natural-language output in an interactive East African prototype.
• Completed the core backend in 12 hours during a 24-hour hackathon, demonstrating rapid delivery under a fixed deadline.

Software Engineering Trainee at Power Learn Project (2024-02 – 2024-06)

• Built full-stack applications across 5 core technologies: Python, JavaScript, SQL, HTML and CSS.
• Connected REST-style backend logic and relational data to browser interfaces, supporting data retrieval and user updates.
• Created Ajirawise, a job-discovery and alert platform that earned 3rd place at the Power Learn Project hackathon.
• Implemented 4 job-alert capabilities: vacancy collection, user-preference filtering, matching logic and notifications.
• Coordinated code changes through Git/GitHub version control, collaborative debugging and iterative project reviews.
• Completed software engineering training across 4 disciplines: backend APIs, databases, frontend development and agile delivery.

Mobile App Development Trainee at TechCrush (2024-03 – 2024-06)

• Built React Native applications for 3 real-world use cases: budgeting, health information and location-aware utilities.
• Translated requirements into shared screens, components and navigation flows across the 3 mobile prototypes.
• Connected React Native interfaces to asynchronous APIs for both reading and updating application data.
• Consolidated repeated screen logic into reusable components and state management, simplifying maintenance across app views.
• Added device and location-aware features to utility prototypes, extending functionality beyond static mobile screens.
• Shipped mobile features in a remote development environment using source control, debugging and iterative feedback.

Associate Degree in Computer Science in Computer Science – University of the People

Bachelor of Science in Civil & Structural Engineering – University of Eldoret