Engineering leadership
Team leader
I lead four engineering teams — eight direct reports and ten offshore engineers — doubling ML model deployments in a single year.
4 Teams8 Direct ReportsCI/CDMentorship
Open to Leadership & Technology Roles
OmarSharaf
AWS Certified
GenAI · RAG
MLOps
Data Engineering
SAFe Agile
Director of Data Engineering · AI/ML & MLOps
Pricing Model Support · Generative AI · Hartford, CT
Seven-plus years in data engineering and AI/ML — leading engineering teams and shipping production Generative AI and machine-learning systems at a Fortune 100 insurer.
0+
Years Experience
0
Teams Led
0
GenAI Apps
2×
ML Deployments
Core Expertise
Where I've worked & what I build with
Databricks
Snowflake
Terraform
Docker
MongoDB
Neo4j
Claude
OpenAI
AI/ML & data
GenAI & MLOps engineer
Production Generative AI and machine-learning systems — RAG applications, real-time and batch models, and enterprise MLOps pipelines.
RAGGPTMLOpsDatabricksSnowflake
Featured Work
All Projects →
Systems I've Built
01
RAG
GenAI RAG Platform
Retrieval-Augmented Generation solutions for context-aware enterprise applications — from the first GPT-3.5 RAG app to three production systems.
3 in production · 5+ PoCs
GPT-3.5PythonRAG
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02
ML
ML Delivery Pipeline
Reusable architectures and deployment patterns for real-time and batch models, doubling production model deployments within a year.
2× deployments · 1 year
AWSCI/CDDatabricks
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03
DDL
DDL Automation Tool
Automated conversion of SQL Server DDLs to a new data storage solution, cutting manual migration effort across the organization.
Migration · automated
PythonSQL Server
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04
Data Lineage Visualization
Neo4j API and frontend to display database hierarchy, improving data visibility for engineering teams.
Graph · lineage
Neo4jAPIFrontend
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05
TST
Automated Testing Framework
Robust testing framework enabling automated tests and repeatable test recreation for future development.
Automated · reusable
PythonTesting
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06
AUT
Python Automation Frameworks
Automation tools and frameworks that reduced development cycle times and saved hundreds of engineering hours annually.
100s of hours saved
PythonREST APIs
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