Applied AI Engineer Cincinnati, Ohio

Varad Parte.

I build AI systems that turn unstructured documents and enterprise data into searchable knowledge, structured outputs, and reliable workflows.

My work spans LLM engineering, retrieval-augmented generation, document intelligence, and agentic automation. I build with Python and Azure, with an emphasis on grounding, evaluation, and human-in-the-loop review.

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Experience

May 2026 – Present

Phillips Edison & Company

AI/ML Developer Intern

Built an internal AI document-intelligence platform using Azure Document Intelligence, OCR, Python, and structured metadata extraction to convert scanned lease PDFs into searchable enterprise knowledge.
Designed and developed custom AI skills that compress recurring IT and business workflows into repeatable, agent-executable tasks, cutting manual effort on routine internal processes.
Built an internal AI Wiki that makes enterprise data AI-ready, structuring business context so AI agents executing business tasks retrieve grounded information rather than inferring it.
Partner with IT stakeholders to deliver strategic AI improvements across Azure Cosmos DB, Azure Logic Apps, Power BI.

Azure Document Intelligence
OCR
Python
Azure Cosmos DB
Azure Logic Apps
Power BI

Jan 2023 – Sep 2023

Phillips Edison & Company

Enterprise Applications Intern

Designed document-ingestion and extraction workflows to normalize OCR output, segment legal clauses, capture metadata, and extract lease terms, dates, and escalation schedules, reducing manual review time by over 53%.
Developed and supported internal business applications using SQL, Python, REST APIs, and database-backed workflows across multiple enterprise teams, improving reliability through expanded QA and audit coverage and contributing to a 27% reduction in application downtime.
Partnered with leasing stakeholders, QA teams, and senior engineers to translate business workflows into automation and validation logic, and built deployment workflows with Python, Power Automate, Azure DevOps, and CI/CD across Dev → QA → Production.

OCR
SQL
Python
REST APIs
Power Automate
Azure DevOps
CI/CD

Projects

Enterprise GenAI Risk & Sentiment Monitoring Platform

Built a GenAI platform that aggregates web and news sources, performs entity matching, and runs diagnostic models to classify sentiment and reputational-risk signals, generating stakeholder-ready reports.
Designed a modular backend using FastAPI, Celery, Redis, and PostgreSQL with provider abstraction, deduplication, confidence-based entity resolution, and structured, auditable metadata.
Implemented LLM-assisted classification, retrieval, alerting/observability signals, and schema-validated structured-output pipelines to support summarization, human review, and decision-making.

FastAPI
Celery
Redis
PostgreSQL

Multi-Agent AI Assistant for Project Management

Architected a multi-agent, tool-using AI assistant with CrewAI, Langflow, and LLM-based orchestration to coordinate Jira operations, ticket routing, and workload distribution.
Built a GPT-based conversational assistant with persistent memory and retrieval to provide project status, dependency insights, and risk-aware natural-language queries.
Designed reusable prompts, context flows, and retrieval patterns that reduced manual project-management effort by 40%.

CrewAI
Langflow
GPT
LLM

Full-Stack Hackathon Operations Platform

Built a full-stack event operations platform (Next.js, Node.js, KeystoneJS, GraphQL) supporting registration, judging, and live-event workflows for hundreds of participants.

Next.js
Node.js
KeystoneJS
GraphQL

Skills

Languages: Python
JavaScript/TypeScript
SQL
Java
C++
.NET
HTML/CSS
Applied AI & GenAI: LLM APIs
RAG pipelines
LangChain
prompt engineering
context design
structured outputs
agentic workflows
CrewAI
Langflow
AI evaluation
hallucination mitigation
human-in-the-loop review
Document Intelligence & Data: OCR
Azure Document Intelligence
document ingestion
metadata extraction
entity resolution
retrieval workflows
sentiment/risk classification
Pandas
NumPy
Backend & APIs: FastAPI
Django Python Framework
Node.js
REST APIs
GraphQL
Celery
Redis
JSON
Frontend: React.js
Next.js
Svelte
TypeScript
Databases: PostgreSQL
MySQL
SQL query design
Supabase
Azure CosmosDB
Cloud, DevOps & Tools: Azure DevOps
Azure Logic Apps
Git
CI/CD
Docker
Kubernetes
Microsoft Power Apps

Education

Aug 2021 – May 2026

Master of Science, Data Science

University of Cincinnati

Accelerated Program · GPA 3.9 / 4.0

Aug 2021 – May 2026

Bachelor of Science, Computer Science

University of Cincinnati

Let’s build something useful.

Connect about applied AI, engineering, or a project you have in mind.

varad.parte@gmail.com