Yanfunmi J.

Key Skills

Software

Other

Top Subject Matter

AI SaaS response pipelines and client-server integration

Backend engineering supporting AI-enabled services (reliability/observability)

Multi-agent AI workflow execution monitoring and scaling

Top Data Types

Text

Image

Computer Code Programming

Top Task Types

Function Calling

Computer Programming/Coding

Freelancer Overview

Forward Deployed Software Engineer — AI-powered SaaS integration (API contracts, response shaping, error handling, state. Brings 2+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal, Proprietary Tooling, and Other. Education includes Bachelor of Science, Obafemi Awolowo University (2027). AI-training focus includes data types such as Computer Code and Programming and labeling workflows including Function Calling, Computer Programming, and Coding.

Labeling Experience

Fullstack Engineer — backend reliability, monitoring, and refactor (V2 release)

Built and integrated backend features for a V2 release to improve API reliability and scalability, which supports productionizing AI-driven services. Implemented modular architecture with dependency injection and strengthened observability with structured logging and monitoring. This work improved operational readiness and reduced incident resolution time for systems that can host AI inference workloads. • Developed backend features for V2 release • Implemented dependency injection modular architecture • Improved reliability with structured logging/monitoring • Performed a full-stack refactor to optimize load time

2025 - 2026

Forward Deployed Software Engineer — AI-powered SaaS integration (API contracts, response shaping, error handling, state sync)

Function Calling

Worked on an AI-powered SaaS platform by defining API contracts and the data flow needed for client-server response shaping and state synchronization. The tasks supported downstream AI inference consumption, including how inference outputs were handled, rendered, and error states managed in the product layer. This role functioned as an AI integration effort ensuring reliable, structured communication between systems that process model outputs. • Defined API contracts and data flow for an AI SaaS platform • Shaped response handling, error handling, and state synchronization logic • Debugged latency and client/server data-consistency issues • Participated in AI model response pipeline architectural discussions

2025 - 2026

Software Engineer — multi-agent workflow integration and AI-output scaling

Other

Integrated real-time agent communication tools across multiple AI workflows and built UI/dashboard components to monitor multi-agent execution. Optimized system performance to handle complex AI outputs at scale, supporting throughput for AI-driven applications. While not stated as ground-truth labeling, the work directly supported operational handling of AI outputs and workflow execution. • Integrated agent communication tools across 5 workflows • Built dashboards and UI components monitoring 5 multi-agent workflows • Optimized performance for 10 complex AI outputs at scale • Coordinated with engineering team to connect tooling to workflows

2025 - 2025

Education

Work History