Sheraz Mahmood

Solutions Architect
Lakeway, Texas • sheraz@00n.ai • LinkedIn • GitHub

Summary

AI-focused architect and researcher with two decades of experience in custom software development and enterprise systems architecture. Specializing in the design and deployment of governable, measurable, explainable, and production-grade AI systems. Proven track record of translating ambiguous business requirements into executable technical strategies, robust architectural decisions, and applied AI solutions.

Professional Experience

Accenture
Associate Director & Solutions Architect

  • Lead architecture and solutioning across complex, enterprise-scale technical environments, drawing on 20 years of foundational software engineering experience.
  • Drive the delivery of practical, production-ready AI systems, bridging the gap between research-only prototypes and scalable organizational solutions.
  • Architect AI governance frameworks, focusing on risk measurement, bidirectional traceability, and evidence-based routing for organizational decision support.

Education & Academic Focus

University of Colorado Boulder
Master of Science in Artificial Intelligence | Expected 2026

  • Current Research Focus: State Estimation for Bidirectional Traceability in Generative Software Architecture.

Research Interests

  • Neuro-symbolic AI & Knowledge Graphs: Integrating symbolic reasoning with neural networks for explainable AI.
  • Control Theory for LLMs: Applying deterministic control mechanisms to large language models.
  • Generative Software Architecture: Repository-state modeling, semantic localization, and deterministic AI systems.

Selected Technical Work & Projects

  • Systems Research: Authored paper-ready research focused on repository-state trees and semantic localization, complete with reproducible artifacts.
  • Evaluation & Calibration: Designed and executed Phase 2 error/support measurement and calibration experiments for applied AI systems.
  • AI Tooling Augmentation: Evaluated Codex augmentation, frozen replay scenarios, and modern AI coding assistants to optimize software engineering workflows.

Technical Skills & Environment

  • Core Competencies: AI Architecture & Delivery, Systems Design, Applied Research, Technical Writing, AI Governance.
  • Languages & Automation: Python, Java, Repository Automation, Evaluation & Calibration scripting.