Custom contact-center software, AI and automation engineered into the platform itself, and deep multi-system integrations. At enterprise scale, handling roughly 625,000 conversations a month. The work is below.
Production software embedded in Genesys where the native client fell short: a custom back-office inbox, a self-serve agent-training app, and the automation pipelines that run daily operations, all under the platform’s own identity and APIs.
AI engineered into operations: conversational-AI vendor integrations (Sierra AI, Kore.ai) wired into live routing and bot flows, plus a Git-backed flow-as-code practice (Archy + CLI-driven promotion between dev and prod) that turns a click-ops org into a version-controlled one.
Conversational-AI agents (Sierra AI, Kore.ai), CRM and ticketing (Salesforce, Zendesk, Jira), HRIS (Workday), and cloud services (AWS), wired into live contact-center flows. Platforms owned end to end, from dev to QA to production, and architected to scale.
Real production builds at enterprise scale. Filter by discipline, or by standard platform mastery vs. custom, out-of-the-box systems.
Not a claim, a log. Twelve months of platform authorship pulled straight from the audit trail: what was built, where, and how much.
Verified backup before any change, read-only credentials by default, hard gates on destructive and production writes, and an append-only audit log over every automated action.
Pre-flight validation that halts a batch rather than corrupting a campaign. Bounded, non-hanging retry on every input. A partial run can never close its own ticket.
State-tracked scheduling that cannot double-fire. A job can run, retry, or overlap a prior run without ever repeating or corrupting work, so reruns are always safe.
Behavior driven by data tables, so a routing, location, or alerting change is a row edit, not a republish. Adding a location or a department is one row.
Logic lives in Data Functions (custom JS/Node) and shared typed modules, not stitched together as low-code data actions. Architect is just the trigger surface, and other engineers' flows consume my modules instead of copy-pasting.
Local rollback snapshots for anything the platform will not read back, prod-mirror QA lattices, and singleton/throttle guards against race conditions under load.
Available for senior Genesys Cloud engineering, with a focus on AI and automation.