Mike Hall

Engaged on a bounded 90-day interim assignment to conduct rapid architecture discovery, platform stabilization, and operational risk assessment for a multi-tenant healthcare SaaS platform serving 130+ clinics following a founder transition.

• Architecture Discovery & Operational Risk Assessment: Built a rapid 90-day system inventory and risk model spanning application codepaths, infrastructure dependencies, access boundaries, and operational risks.
• Production & Compliance Governance: Established release verification gates across the deployment pipeline of a platform servicing 130+ clinics, 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 legacy modernization with production stability, OpenTelemetry observability, and cross-team technical direction.

• Technical Leadership & Team Consolidation: Progressed from Digital Origination Team Lead to Software Architect for the Acquisition Lane, merging two attrition-impacted teams into a unified, high-functioning engineering unit before converting to Associate Director, Staff Engineer upon corporate architecture track restructuring.
• ACQ Enablement Founding & Engineering Mandates: Founded and technically led the ACQ Enablement team to protect core engineering concerns from product feature pressure: driving platform stabilization, legacy modernization, system process mapping, architecture documentation, PII remediation, and fraud investigations.
• Observability & Enterprise Trace: Founded and led the OpenTelemetry Working Group (OTel WG) to establish the Enterprise Trace across high-volume Instant Prequalification flows, connecting onemain_frontend, Rails acquisition services, MuleSoft, and IBM mainframe backends to eliminate blind spots and align engineering around real-time service maps.
• State Machine Refactoring & Data Integrity: 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.
• 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.
• 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.

Built and operate three MCP (Model Context Protocol) servers that expose live system state as callable tools to any MCP client, alongside the Claude Code skills, context-isolated subagents, and commit-time checks that keep agent work bounded and reviewable.

• Bidirectional Knowledge Server: Built ctx-mcp, an MCP server fronting a PostgreSQL knowledge suite that agents both query and write back to, so methodologies and lessons learned in one session are retrievable in the next rather than re-derived.
• Telemetry-Driven Diagnosis: Built o2-mcp, exposing on-demand OpenObserve telemetry (errors, slow spans, failed jobs, distributed traces) as agent-callable tools, so an agent diagnoses a running system from observed behavior instead of inferring from source.
• Compliance-Safe Observability: Telemetry reaches agents already PHI-scrubbed at the OpenTelemetry ingest edge, keeping a compliance-sensitive platform debuggable by an AI without exposing protected data.
• Local Inference Tooling: Built llama-mcp, exposing a local llama.cpp inference stack as callable tools for interrogation and validation, keeping routine inference on-box.
• Context as a Budgeted Resource: Designed context-isolated subagents that keep high-volume audit work out of the main conversation's context window, with per-client registration tooling and pre-commit hooks that reject any agent asset that isn't self-describing.

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.

Recorded, and later restored, an archive of 214 technical interviews with practitioners from the Ruby, JVM, and Software Craftsmanship movements, using a local-only AI pipeline to transcribe, structure, and cross-link two decades of primary-source material into a searchable knowledge graph.

• Local-Only AI Restoration Pipeline: Built a Whisper and local-LLM pipeline that transcribes, diarizes, and structures long-form interview audio entirely on-device, keeping a large private media corpus off third-party inference services.
• Schema-Validated Content Platform: Runs on a contract-validated data layer: every interview, asset, and transcript is checked against an explicit schema at build time, with referential-integrity checks that fail the build rather than publishing broken data.
• Semantic Cross-Linking & Taxonomy Generation: Generates a topic taxonomy, knowledge graph, and semantic cross-links across the corpus, turning an unstructured media archive into navigable, individually indexed pages.
• Primary-Source Capture: Conducted the original interviews on-site at GOTO Conference, Software Craftsmanship North America, RailsConf, and WindyCityRails, with practitioners including Dave Thomas, Stuart Halloway, Corey Haines, Sandro Mancuso, and Micah Martin.
• Digital Archaeology: Recovered and reconstructed material from defunct platforms and web archives, reconciling incomplete metadata across sources to restore provenance for recordings that would otherwise have been lost.