Mike Hall

Target Focus: Refactored multi-step Rails acquisition workflow state machines, eliminating lateral state corruptions in high-volume customer prequalification pipelines.

• 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 customer acquisition flows, connecting a complex Rails distributed monolith, MuleSoft, and IBM mainframe backends to eliminate blind spots and align engineering around real-time service maps.
• 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.

Target Focus: Sequenced zero-downtime Ruby and Rails version upgrades, optimized MySQL full-text search indices, and built batch Sidekiq/SendGrid delivery pipelines.

• 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.
• 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.

Target Focus: Refactored monolithic Rails data layer, executing multi-database partitioning across PostgreSQL and MySQL with dual-write synchronization.

• Legacy Boundary Isolation: Decoupled critical legacy constraints behind explicit service boundaries, eliminating high-risk direct database dependencies and establishing clean execution paths.
• Data Access & Query Optimization: Replaced ad-hoc global state access with structured query patterns and multi-tier caching strategies, accelerating throughput for high-volume database reads.
• Frontend Test Hardening: Hardened the Ember.js frontend test suite across complex CRM user workflows, enforcing testable state boundaries and reducing regressions in customer-facing flows.
• Test-Driven Observability: Established test-driven observability patterns across legacy PHP codepaths, shortening developer feedback loops during high-risk production debugging.

Target Focus: Integrated Chargify recurring billing and standardized multi-VM local development environments via Vagrant.

• Integrated the Chargify subscription payment platform, launching self-service recurring billing and account management.
• Standardized local development environments using multi-VM Vagrant orchestration, eliminating developer environment drift against production.

Target Focus: Implemented custom tracking analytics and automated staging/production deployment pipelines for high-traffic consumer web products.

• Implemented custom tracking and analytics tools, enabling targeted monetization and direct platform revenue.
• Standardized automated testing and staging environments, establishing reliable continuous integration across the engineering team.
• Streamlined AWS deployment pipelines and server images, eliminating deployment downtime during peak consumer traffic spikes.

Rails 8 platform for multi-source job ingestion, semantic matching, and application automation, built as a working laboratory for local-first LLM orchestration and treating scraped third-party text as hostile input.

• Data Ingestion & Normalization: Built a multi-source Rails ingestion pipeline and PostgreSQL storage schema, unifying fragmented job market datasets for structured downstream analysis.
• Semantic Search & Matching: Implemented vector search embeddings via pgvector, enabling high-precision semantic matching between complex candidate profiles and job requirements.
• Local-First AI Orchestration: Designed a provider-agnostic LLM orchestration layer behind a YAML-driven model registry, local-first by default (llama.cpp/Ollama primary, hosted Claude as fallback), so routine inference never leaves the machine while a stronger hosted model can be selected per call site.
• Prompt Injection Defense: Built a four-stage guardrails pipeline (normalize, weighted heuristic scan, risk classify, output validate) screening every untrusted scraped document before it reaches a model, scoring known injection patterns plus an instruction-density heuristic to secure ingestion against hostile inputs.
• Browser Extension & Lifecycle Capture: Built an MV3 Chrome extension with 16 provider adapters that extracts postings from live ATS pages and captures the full application lifecycle (questions asked and answers given) back into the platform.
• Static Signal Integration: Injected static analysis rules and architectural constraints into model context windows, preventing drift between generated outputs and system security contracts.

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.

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.
• 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.