GenAI and Data Engineer

Tenacious Intelligence Corp.

2024 - Present
California, USA

Lead AI initiatives for autonomous systems, managing a team of 8 engineers and delivering production ML models serving 10M+ users daily.

Key Achievements:

  • 1
    Directed a team of AI engineers in creating a legal AI assistant using multi-agent architecture (Autogen), projected to enhance legal research efficiency by up to 10x for an Italian law firm.
  • 2
    Engineered a Python-based data pipeline for complex legal datasets, processing over 80GB into Weaviate and developing LLM-generated schemas to improve Retrieval-Augmented Generation (RAG) accessibility.
  • 3
    Developed an AI-powered survey management system (Django, Next.js), automating analysis and reducing survey data processing time from days to seconds, significantly cutting associated costs.
  • 4
    Instituted a data warehouse (PostgreSQL, Kedro, dbt) and Redash dashboards for a content creator, achieving an 80% satisfaction rate from senior management by enhancing data visibility for strategic decisions.
  • 5
    Managed FastAPI and Go/MongoDB backend integrations for AI services, ensuring robust support for applications managing large-scale user interaction and data processing.

Products & Projects

Legal AI Assistant

Product

A legal AI assistant using multi-agent architecture (Autogen), projected to enhance legal research efficiency by up to 10x for an Italian law firm.

Details

As a GenAI and Data Engineer at Tenacious Intelligence Corp., I lead the development of our flagship Legal AI Assistant that enables real-time decision making for an Italian law firm. My responsibilities include architecting scalable ML pipelines, optimizing model performance, and mentoring junior engineers. I collaborate closely with product managers to translate business requirements into technical solutions and with DevOps to ensure smooth deployment and monitoring of ML models in production.

Survey Management System

Product

An AI-powered survey management system (Django, Next.js), automating analysis and reducing survey data processing time from days to seconds, significantly cutting associated costs.

Details

Led the project from wireframing and schema design to full implementation, creating a comprehensive survey management platform using Django (backend) and Next.js (frontend).

Technical Summary

Data Analysis for a Children's Content Creator (Ubongo)

Product

Data analysis for a children's content creator (Ubongo) to improve their content creation process and engagement. Provide the management team with deep, actionable insights from disparate company data sources, including content, HR, and financials.

Details

Architected a data infrastructure using PostgreSQL and built interactive, insightful dashboards using Redash. Employed Kedro and dbt for robust data pipeline management and transformation, ensuring continuous and automated updates directly from the company's file servers.