Khoa Q

Customers needed a secure AI platform capable of orchestrating multiple agents and retrieving national security vulnerable classified enterprise data reliably at scale

Development of a multi-agent RAG platform integrating LLMs, retrieval systems, custom MCP servers, and RBAC-controlled access for structured and unstructured classified data.

Helped secure Microsoft’s first classified Azure OpenAI deal ($20M), contributed to $23M+ delivery revenue, and built a high-performance platform adopted across agencies and contractors.

Operators struggled to securely retrieve and interact with both structured and unstructured classified enterprise data across disconnected systems.

Engineered retrieval pipelines and custom MCP server integrations within a multi-agent AI platform, enabling secure LLM interaction with enterprise data using RBAC-controlled access.

Improved secure data accessibility and orchestration performance across classified environments, contributing to platform feature adoption across new/existing customers utilizing the platform application. i.e $900k/yr cloud revenue and $5M commited cloud consumption for the single customer engagement requesting the additional use case

Customer needed a new AI mobile/web platform built from 0→1 under an aggressive timeline that could securely operate across iOS, Android, and Web platforms. Existing engineering teams lacked experience with modern cross-platform application & mobile development.

Steered 0→1 architecture design across mobile/web application, API development, and cloud systems, selected the cross-platform tech stack, established the iOS development setup, and guided engineers on new technologies to rapidly deliver a unified AI platform adaptable to multiple mission environments.

Accelerated development of a cross-platform AI application for 6,000+ federal users, reduced engineering ramp-up time for new technologies, and enabled rapid delivery of a scalable, cloud-native platform capable of supporting future enterprise expansion and mission-critical operations.

Customers struggled to securely deploy containerized AI solutions in highly regulated government environments while meeting strict compliance and security requirements.

Developed an internal platform prototype for deploying secure containerized AI applications with automated vulnerability scanning and AI-driven compliance analysis. Contributed in demos, training, and marketing content.

Accelerated secure AI deployment readiness, increased stakeholder confidence during customer demos and technical evaluations, and strengthened positioning for future 6–7 figure government AI contracts.

AI Application was 'unusable' in commercial cloud environments due to regulation and compliance.

Designed and deployed secure Azure Government IL4+ cloud infrastructure supporting AI applications tailored to mission-specific constraints while streamlining deployment and integration workflows.

Accelerated 0-to-1 deployment timelines for new AI platform customers, increased infrastructure adoption for secure AI applications, and helped secure customer contracts by demonstrating rapid deployment and integration capabilities.

Multiple classified programs relied on outdated artifact management, fragmented deployment pipelines, and vulnerable third party DevOps tools.

Co-led migration from Artifactory to Nexus, developing CI/CD pipelines, and automated release engineering process in air gapped environments.

Improved DevSecOps scalability across 4+ programs - increased deployment and release efficiency by over 400%.

A customer needed a secure AI mobile/web platform to deliver national classified information to users during daily operations and crisis events.

Helped spearhead customer requirement scoping, designed the initial technical architecture and stack, collaborated directly with stakeholders on UX/branding, and delivered solution demos aligned to mission workflows.

Accelerated adoption of AI-driven classified information delivery, improved operational responsiveness during national crisis events, and established a scalable foundation for enterprise-wide platform expansion.

A customer lacked a clear vision for how AI could modernize mission workflows, and their existing application was not designed for cloud-native scalability.

Migrated applications to the cloud and built a demo-ready AI-enhanced version of their application months ahead of schedule, translating ambiguous customer requirements into production-ready solutions.

Unlocked cloud and AI modernization opportunities tied to a multi-year transformation strategy and contributed to $2.1M in revenue.

Customers needed rapid deployment of secure cloud infrastructure under mission-specific constraints.

Served as the primary technical POC - pre/post sales, adapting deployments to customer environments while facilitating knowledge transfer and operational alignment.

Platform IP adopted across contractors, branches, and agencies contributing to $25M+ in delivery revenue across customers and 6 figure average yearly cloud consumption revenue.