Senior Full-Stack / AI EngineerSenior Full-Stack / AI Engineer

Key Achievements:

Monitor [number] API requests daily across Python and FastAPI services to maintain reliable high-throughput processing. • • • • • Track [number] distributed AI evaluation runs weekly to support resilient backend processing and timely model validation. Engineer resilient backend systems for distributed AI evaluation and high-throughput processing sequences. Develop production-grade APIs and full-stack applications with Python, FastAPI, Next.js, PostgreSQL, and Redis. Revamp backend services to improve scalability, maintainability, and reliability across production workflows. Coordinate architecture planning, implementation strategies, and technical reviews through asynchronous collaboration

Key Achievements:

• 01/2024 - Current Reduce monthly query latency by 9% in database-heavy backend services for faster evaluation tool responses. • • • • Track weekly pipeline uptime at 9% across asynchronous evaluation workflows to support reliable AI assessment processing. Build scalable evaluation tools and dashboards that support AI assessment workflows end to end. Optimize asynchronous processing pipelines to improve throughput and keep backend services responsive. Introduce Git-based collaboration, resolve technical issues, and automate CI/CD deployment processes

Key Achievements:

Monitored 10% pipeline uptime weekly for high-volume data processing workflows. • • • • Resolved 9 production incidents weekly across backend services to maintain service stability. Engineered distributed backend services supporting AI infrastructure and reliable request handling at scale. Built high-volume data processing pipelines that supported faster, more consistent production workflows. Improved system scalability in production environments by optimizing service architecture and throughput.

Key Achievements:

• 02/2022 - 01/2023 Resolved 10 incident tickets monthly for machine learning and NLP applications in production. • • • • Tracked 10% API uptime weekly across cloud-based production services supporting analytics workflows. Developed and released machine learning and NLP applications within cloud-based production environments. Designed scalable APIs and backend services for analytics workflows and real-time computation systems. Supported model deployment, debugging, and refactoring to improve reliability across releases