I’m a Software Engineer focused on building reliable, scalable AI-driven infrastructure. I currently work at a Fortune 500 financial institution, where I design tooling that sits at the intersection of AI systems, data validation, and test infrastructure.

While my background includes test automation at scale, my long-term focus is firmly rooted in backend engineering and and applied AI — especially building tooling that makes complex systems observable, verifiable, and safe.

I’m especially interested in:

• AI Infrastructure & Evaluation
• Developer Tooling & Automation
• High-leverage engineering problems

November 2025 – Present

• Design and build data analytics tooling using Python, Pandas, and Streamlit to surface safety, accuracy, and consistency metrics across enterprise AI systems.
• Develop automated validation frameworks that cross-reference AI outputs across S3 artifacts, Salesforce data, and internal services, ensuring traceability and response integrity.
• Contribute to early exploration of AI evaluation pipelines, model behavior analysis, and governance-focused tooling for production AI use cases.
• Investigating Model Control Protocol (MCP)–based architectures to safely connect AI models with proprietary systems and automated development workflows.

October 2024 – November 2025

• Led development of scalable UI and API test infrastructure using Playwright, TypeScript, and Cucumber, supporting high-impact enterprise applications.
• Built and maintained CI/CD regression pipelines leveraging GitLab CI, AWS Lambda, DynamoDB, and S3.
• Served as a technical interviewer and led rapid onboarding of a team of QA engineers for a time-sensitive, high-profile deliveries.
• Acted as a technical owner for automation strategy, framework design, and reliability improvements across projects.

• Studying software design patterns, modern C++, and systems-oriented architecture.
• Actively practicing DSA and problem-solving with a focus on correctness, performance, and tradeoffs (LeetCode + competitive programming).

• Deepening hands-on experience with AWS (Lambda, DynamoDB, S3) as foundational building blocks for backend and AI tooling.
• Designing event-driven and data-oriented systems to support automation and evaluation pipelines.

• Working with data preparation, evaluation metrics, and model interaction pipelines.
• Exploring MCP-style AI orchestration , particularly for automated testing and regression analysis.

Languages
Python · TypeScript · JavaScript · C++ · Java · SQL

Frameworks & Tooling
Playwright · FastMCP · Next.js · Node.js · Streamlit · Git · FastAPI

Cloud & Platforms
AWS (Lambda, DynamoDB, S3) · GitHub Actions · GitLab CI/CD · Salesforce · Fly Machines · Docker

Engineering Practices
CI/CD · OOP · Async Programming · Automation Framework Design · System Reliability

• 🔗 https://www.meltonshomeandauto.com
• Built and maintain a production Next.js web application for my family’s automotive business.
• Own the full lifecycle: development, hosting, updates, and online presence management.
• Stack: Next.js, TypeScript, React, Tailwind CSS

• 🔗 https://www.blaisemoses.com
• Central hub for my projects, writing, and technical explorations across software engineering, AI, and systems topics.
• Stack: Next.js, TypeScript, React, Tailwind CSS

Anything worth doing is worth doing all the way.
Don’t mistake a plateau for the peak.

• 📧 Email: bamoses2001@gmail.com
• 💼 LinkedIn: https://www.linkedin.com/in/blaise-moses