Daniel Z.

Key Skills

Software

No software listed

Top Subject Matter

LLM/RAG pipeline for analytics insights

Top Data Types

Computer Code Programming

Top Task Types

Text Generation

Freelancer Overview

Software Development Engineer (Backend) — RAG pipeline development. Brings 10+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include OpenAI. Education includes Bachelor of Science, Stratford University (2017). AI-training focus includes data types such as Computer Code and Programming and labeling workflows including Text Generation and Fine Tuning.

Labeling Experience

Software Development Engineer (Backend) - Amazon

You modernized and scaled legacy Django monoliths into high-performance, modular services by leading migrations to the latest Django versions and refactoring toward domain-driven architectures. You implemented asynchronous task processing and event-driven patterns to improve reliability, reduce latency, and support integration with high-throughput FastAPI/Flask microservices. You also built a production RAG pipeline using OpenAI models to transform large analytics datasets into real-time, actionable insights. • Led backend modernization efforts across Django applications • Developed event-driven and asynchronous processing workflows • Built and optimized vector search, retrieval, and prompt engineering • Integrated monitoring with Prometheus and Grafana to improve uptime

2024 - 2026

Software Development Engineer (Backend) — RAG pipeline development

Text Generation

Built and productionized a Retrieval-Augmented Generation (RAG) pipeline using OpenAI models to convert large-scale analytics data into real-time, actionable insights. Optimized vector search, retrieval, and prompt engineering to improve the quality and usefulness of generated outputs. The work reduced manual analysis effort and accelerated decision-making for downstream teams. • Designed and implemented retrieval components for RAG workflows. • Engineered prompts and tuned RAG behavior for analytics use cases. • Evaluated and iterated on model output reliability and relevance. • Integrated the pipeline into an event-driven microservices environment.

2024 - 2026

Education

Work History