Automation Specialist and Workflow Architect with expertise in designing intelligent low-code solutions to streamline enterprise operations. Proven track record of integrating n8n, Airtable, and Large Language Models (LLMs) to eliminate manual data entry and optimize administrative pipelines. Skilled in leveraging Vision AI and RAG architectures to transform unstructured data into actionable business intelligence for logistics and recruitment sectors.
Automation & Orchestration: n8n (Self-hosted), Webhooks, JSON Data Handling, REST API Integration
AI & Machine Learning: Google Gemini API, OpenAI API, RAG, Prompt Engineering, Pinecone, Computer Vision/OCR
Data Management: Airtable (Advanced Schema Design, Automations), Document Parsing
Web Development: React, Next.js, HTML, CSS
Fleet Operations & Factoring Automation
Automation Architect
- Centralized Operations Database: Architected a custom Airtable schema to serve as the single source of truth for fleet drivers, vehicle statistics, and active loads, successfully replacing fragmented spreadsheet tracking.
- Automated Document Processing: Engineered an n8n workflow utilizing Google Gemini Vision API to ingest and parse complex Rate Confirmations and Bills of Lading (BOLs), extracting critical financial data with high accuracy.
- Inspection Compliance Pipeline: Developed a Telegram-triggered ingestion system that processes driver inspection photos via Vision AI, validating unit numbers against fleet records and automatically logging compliance data.
- Financial Velocity: Automated the compilation and submission of factoring documents to MyTriumph immediately upon load completion, significantly accelerating payment cycles and reducing administrative overhead.
Autonomous Job Market Intelligence Agent
Automation Engineer
- Data Aggregation Pipeline: Built a robust scraping pipeline using n8n and JSearch API to aggregate and standardize 100+ job listings per execution from multiple platforms.
- AI-Driven Candidate Screening: Integrated Gemini 2.5 Pro to analyze job descriptions against candidate profiles, implementing logic to identify visa/clearance blockers and calculate "fit scores" based on technical stack overlap.
- Application Optimization: Engineered a keyword injection system that dynamically rewrites resume bullet points to mirror ATS requirements, increasing application relevance without fabricating experience.
- Operational Efficiency: Reduced manual job search and application time by approximately 95% by automating the qualification, data extraction, and document tailoring phases.
Personal Knowledge Engine (RAG System)
Automation Architect
- Intelligent Content Ingestion: Engineered a Slack-triggered workflow that fetches URLs and raw text, utilizing LLMs to strip HTML noise and convert content into clean Markdown for processing.
- Vector Database Architecture: Designed a Pinecone vector database implementation with embeddings to chunk and index technical documentation, enabling semantic search capabilities.
- Conversational Retrieval Interface: Built a chat-based RAG (Retrieval-Augmented Generation) system using Gemini 2.5 Pro that synthesizes contextual answers from the private knowledge base, citing original sources to ensure accuracy.
- Knowledge Management: Established a "save once, query forever" pipeline that eliminates manual tagging and folder organization for research and technical notes.
Master of Science in Computer Science
Campbellsville University
Bachelor of Science in Computer Science
Koneru Lakshmaiah Education Foundation