Mike Hall

Engaged to conduct rapid system discovery and operational risk assessment for a multi-tenant healthcare SaaS platform serving 130+ clinics following a founder transition.

• Architectural & Risk Cartography: Built a rapid 90-day system inventory and risk model spanning application codepaths, infrastructure dependencies, access boundaries, and operational risks.
• Production & Compliance Governance: Protected production stability across 130+ clinical environments by establishing release verification gates across the deployment pipeline, blocking unvalidated changes prior to HIPAA compliance review and business sign-off.
• Engineering Continuity: Created transparent component ownership, visible operational priorities, and collaborative decision rhythms for a distributed U.S.-Mexico engineering team.

Served as Senior Technical IC and Software Architecture Lead for the Acquisition lane of a regulated financial enterprise, combining hands-on system cartography with production stability, modernization, observability, and cross-team technical direction.

• Full-Stack Dependency Cartography: Reconstructed end-to-end customer journeys spanning browser interaction surfaces, API gateways, application middleware, and legacy database layers, establishing a unified operational risk model for incident response and change governance.
• Incident Response & Technical Escalation: Served as final escalation point for high-severity outages, translating live root-cause investigations into stronger telemetry, explicit component ownership, and reusable system knowledge.
• Lateral State Coupling De-risking: Refactored fragile multi-step Rails workflow state machines, eliminating hidden lateral state mutations across asynchronous boundaries and resolving persistent data integrity failures in core acquisition flows.
• Platform Enablement & Responsibility Realignment: Realigned Acquisition engineering around explicit business boundaries, then founded and technically led ACQ Enablement to protect platform reliability, remediation, and modernization work from feature pressure.
• Observability & Boundary Instrumentation: Founded and led an enterprise OpenTelemetry initiative, instrumenting legacy microservices and third-party API supply-chain boundaries to convert dark system behavior into quantifiable telemetry and reduced MTTD.
• AI-Augmented Systems Investigation: Introduced privacy-conscious local AI workflows for legacy code analysis and engineering support, expanding investigative capacity while keeping human review, security constraints, and source evidence explicit.

Led backend stability, performance, and modernization for high-traffic Rails products, improving full-text search, campaign delivery pipelines, and data layer reliability while systems remained under production load.

• Search Infrastructure Simplification: Replaced legacy external search clusters (Sphinx) with native MySQL full-text search and optimized relational indices, eliminating external service dependencies and reducing platform infrastructure footprint.
• High-Volume Messaging Pipelines: Designed and validated asynchronous batch delivery pipelines via SendGrid and Sidekiq, enforcing IP warmup protocols and deliverability safety for large-scale campaign operations.
• Data Engine & Analytics: Engineered complex relational analytical queries across multi-million row content catalogs, powering real-time data visualizations and international media publishing.
• Zero-Downtime Platform Upgrades: Led Ruby and Rails framework upgrades across multiple core applications, sequencing database migrations and dependency updates to maintain uptime during platform modernization.

Designing and building a real-time tactical game platform as a current hands-on laboratory for deterministic systems, product architecture, and controlled AI-assisted engineering.

• Designed a deterministic engine with replayable action logs and server-authoritative state transitions, making complex outcomes reproducible and independently verifiable.
• Built replay validation, adversarial coverage, and CI verification gates so state transitions can be checked across the complete lifecycle.
• Uses controlled agent workflows with bounded tasks, acceptance criteria, automated checks, and human-reviewed outputs rather than treating model output as authority.