Maaz G.

Key Skills

Software

Other

Top Subject Matter

Document intelligence and RAG-based CRM automation

AI tutoring and learner engagement/recommendation systems

Legal Services & Contract Review

Top Data Types

Document

Text

Top Task Types

Text Generation

Transcription

Freelancer Overview

Senior Software Engineer, K9Bookkeeping — Built distributed AI document-processing and RAG pipelines. Brings 6+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Internal, Proprietary Tooling, and Other. Education includes Bachelor of Science in Software Engineering, Superior University. AI-training focus includes data types such as Document and Text and labeling workflows including Text Generation, Evaluation, and Rating.

Labeling Experience

Senior Software Engineer - K9Bookkeeping

TextTranscription

Led a remote team of engineers to deliver production-ready features on a biweekly sprint cadence, owning backend architecture decisions and CI/CD pipelines. Architected and optimized scalable ETL pipelines for migrating and processing large document and record volumes into AWS S3 to support downstream AI workflows. Built distributed document-processing solutions using Python ML scripts, OCR-driven extraction, and LlamaCloud orchestration to improve performance and reduce manual effort. • Managed engineering execution, delivery planning, and backend architectural tradeoffs • Designed CI/CD workflows and automation for reliable releases • Implemented data ingestion and transformation pipelines at multi-million scale • Integrated OCR and LLM services to accelerate document processing and retrieval

2025 - Present

Senior Software Engineer, K9Bookkeeping — Built distributed AI document-processing and RAG pipelines

DocumentText Generation

Built an OCR-driven document-processing pipeline that extracts information for downstream RAG workflows using LlamaCloud and Python ML scripts. Designed AI integration around document intelligence to reduce manual document lookup for operational teams and improve retrieval quality. Optimized pipeline performance to cut processing time and reviewer effort while maintaining accuracy for CRM-related workflows. • OCR-based extraction workflow design for unstructured documents • RAG pipeline integration with LangChain orchestration and OpenAI APIs • Retrieval accuracy improvements (90%+ retrieval accuracy) and reduced manual lookup • Performance gains including 65% processing-time reduction and 80% lower manual review effort

2025 - Present

Associate Software Engineer, AURLAB — AI training platform with engagement tracking and recommendations

OtherText

Developed AI-driven engagement tracking and personalized recommendations within a Python-based training platform to improve course completion outcomes for learners. Created supporting recommendation and monitoring services via REST APIs to reduce manual progress tracking effort. Automated reporting workflows using cross-functional collaboration to reduce administrative overhead. • AI-driven learner engagement tracking and personalization • Recommendation engine API development and performance monitoring • Reduced manual student progress tracking by 60% • Automated reporting workflows for usability improvements

2021 - 2022

Education

Work History