Systems Architect · Healthcare Compliance & GRC

• High-Volume B2B Settlement Engines: Engineered scalable financial reconciliation infrastructure that normalizes SWIFT, M-Pesa B2B, and SAP ERP data streams into secure PostgreSQL registers.
• Cash-Flow Accuracy & Capital Optimization: Built discrepancy-tracking triggers that isolate structural transaction breaks and reduce manual audit review by an estimated 90%.
• Tenant Isolation & Rapid Delivery: Deployed PostgreSQL Row-Level Security for strict per-user boundaries and connected component-driven AI engineering environments to CI/CD pipelines.

• Structural Bottleneck Remediation: Audit large-scale enterprise networks to identify friction points and engineer modern application-integration pathways.
• Governance & Control Monitoring: Build policy-to-control maps and SOPs that transition higher-risk data practices into secure, audit-ready workflows with retention and encryption patterns.

Multi-channel financial reconciliation platform normalizing SWIFT registry, M-Pesa B2B, and SAP ERP data streams into secure PostgreSQL registers with role-based access control and full audit logging.

• Automated discrepancy-detection triggers cut manual audit review by ~90%
• Data classification, retention, and encryption controls mapped to HIPAA & SOC 2 objectives
• Risk register and data-flow documentation used in vendor due diligence

Walkable production prototype of the settlement pipeline: load expected settlements, ingest SWIFT / M-Pesa B2B / SAP ERP feeds, run reconciliation, and remediate exceptions against real PostgreSQL records — with a public read-only JSON snapshot for reviewers who prefer raw data.

• Per-visitor session isolation; all direct table access restricted to backend service-role policies
• Automated exception detection for amount, currency, orphan, and missing-settlement breaks
• Public read-only endpoint at /api/public/reconciliation-demo — synthetic data, no login, no writes

Production web platform with authenticated, per-user data isolation (Postgres row-level security), server-side AI generation, and LinkedIn integration — the same access-control patterns used for PHI-bearing systems.

• Per-user tenancy enforced at the database layer, not the UI
• AI-tailored, ATS-optimized resume versions and cover letters per job listing
• Server-only secrets and least-privilege access throughout

Enterprise-wide evaluation of state records and data-handling workflows against public-records, confidentiality, and retention policy — producing SOPs, control monitoring, and remediation pathways for modern software integrations.

• Risk assessments and control monitoring for restricted data systems
• Policy requirements translated into technical system requirements
• Audit-ready SOP documentation