Faith J.

Key Skills

Software

No software listed

Top Subject Matter

AI-powered messaging

Nlp Domain Expertise

Rag Domain Expertise

Top Data Types

Text

Top Task Types

Prompt + Response Writing (SFT)

Text Generation

Freelancer Overview

Full Stack Engineer Intern — Leasey.AI (Twilio messaging + LLM/RAG integration). Brings 4+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include LangChain, LlamaIndex, and FAISS. Education includes Bachelor’s Degree in Computer Science, University of Toronto (2025). AI-training focus includes data types such as Text, Computer Code, and Programming and labeling workflows including Prompt + Response Writing (SFT), Text Generation, and Computer Programming.

Labeling Experience

Full Stack Engineer Intern — Leasey.AI (Twilio messaging + LLM/RAG integration)

TextPrompt + Response Writing (SFT)

Built and integrated AI-powered messaging features into production systems using LangChain, LlamaIndex, and NLP pipelines for semantic search and knowledge retrieval. Applied Retrieval-Augmented Generation (RAG) with FAISS to generate or support responses grounded in internal documents and support knowledge. Implemented chatbot automation workflows that classify intents, summarize messages, and assist support operations using LLM APIs. • Data involved: internal knowledge text and conversational/message content • Labeling/AI training task type: creating prompt/response interactions and LLM-driven conversational outputs • Output types: summaries, intent classifications, and response generation • Evaluation/operational integration into messaging workflows

2025 - 2026

Full Stack Developer Intern — Odai (Django/React platform work)

TextText Generation

Developed a consumer ecommerce platform using Django and React, including backend APIs for authentication, cart, and checkout flows. While the role is primarily software engineering, it contributed to application logic that could support AI-assisted or text-processing features at the platform level. No explicit data labeling, annotation, or AI training datasets are described. • Data involved: transactional and user text data via RESTful APIs • Labeling/AI training specifics: not explicitly stated • Software engineering support for potential AI use cases • Limited evidence of direct labeling or annotation work

2024 - 2024

Web Developer Intern — Acephalt (web development, SQL optimization)

Built responsive web interfaces for financial applications using PHP (Laravel), WordPress, and JavaScript. Implemented and optimized backend integrations and SQL query performance for reporting and portfolio management. No explicit data labeling, annotation, or AI training activity is described. • Data involved: reporting and portfolio information handled in web apps • Labeling/AI training specifics: not stated • Focus: UI, backend APIs, and SQL optimization • Limited evidence of direct AI/data-labeling responsibilities

2023 - 2024

Education

Work History