Suraj Sheela
Software Engineer • Cloud/DevOps • AI
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Experience

Work

A few roles where I shipped production-grade systems across automation, observability, data pipelines, analytics, and secure APIs.

University of North Texas
UNT System
•
Denton, TX • Dec 2021 – Present
Software Systems Engineer
Cloud/DevOpsAutomationSQL + Power BICI/CDInfra
  • Built Practice Management analytics on Microsoft SQL Server by querying, cleaning, and modeling 15,000+ legal matter records across 40+ attorneys and 10+ practice areas; delivered Power BI dashboards with reliable refresh cycles, reducing ad-hoc SQL/Excel reporting ~60%.
  • Modernized CI/CD and infrastructure automation with Docker, Kubernetes, and IaC; introduced parallel test runners + environment segregation to reduce build times ~29% and post-deploy defects ~11% across 1,500+ endpoints.
  • Developed a Python-based DocuSign ingestion + reporting pipeline using OAuth (JWT/RS256) across NA1–NA4; automated monthly exports (~50,000+ envelopes/year), normalized schemas, and published datasets for reporting, cutting manual turnaround ~70%.
UNT System — Business Service Center
TaskUs
TaskUs
•
Dallas, TX • Jun 2024 – Aug 2024
AI Applications Developer Intern
AI AppsSalesforceAutomationAPIsData + Insights
  • Shipped “Byte,” an AI-powered chatbot and workflow tooling; built custom Salesforce logic to support lead/opportunity creation and performance tracking, reducing manual effort and improving adoption during testing.
  • Integrated large datasets into Salesforce Einstein AI lead/opportunity scoring and pipeline inspection to improve prioritization and forecasting workflows.
  • Led UAT and surfaced critical issues early; contributed UI/UX changes that made workflows cleaner and reduced user friction for day-to-day operations.
TaskUs team
University of North Texas
University of North Texas
•
Denton, TX • 2022 – 2025
Undergraduate Teaching Assistant (Computer Science)
TeachingDSASystemsMentorshipLeadership
  • Mentored hundreds of students across programming and algorithms through labs, office hours, and code reviews; improved student outcomes by reinforcing fundamentals with practical debugging and problem-solving.
  • Delivered high-clarity walkthroughs for core CS concepts (data structures, runtime analysis, recursion, OOP), helping students build confidence and consistency under deadlines.
  • Supported course operations end-to-end: grading, rubric alignment, exam review sessions, and targeted help for students who were falling behind.
Computer Science lab