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 safety across 130+ clinical environments by establishing explicit release verification gates for 36+ pending platform updates, ensuring unvalidated changes were blocked prior to business sign-off and HIPAA compliance review.
• 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.

• Replaced complex, outdated external search dependencies (Sphinx) with native MySQL full-text search and optimized relational queries, simplifying deployment and reducing platform infrastructure footprint.
• Built and validated high-volume asynchronous messaging pipelines (SendGrid async batching) and managed IP warmup protocols for large-scale marketing campaign operations.
• Authored complex analytical SQL queries powering data-driven infographics and international media coverage for high-volume content catalogs.
• Led hands-on Ruby and Rails upgrades across multiple applications, sequencing legacy remediation to maintain service continuity through high-risk platform transitions.

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.