• Designed and shipped a new real-time meeting bot architecture for AI recording/analysis, reducing bot join latency by 65% and improving reliability across edge cases in production.

• Built a real-time streaming ingestion pipeline (Zoom RTMP) to power transcription workflows, cutting end-to-end processing latency by 30% and improving throughput under load.

• Implemented resilient streaming and asynchronous processing patterns (backpressure, retries, graceful recovery) to keep real-time pipelines stable during network variance and provider hiccups.

• Shipped instructor/admin-like internal tooling (impersonation + diagnostics) that accelerated QA, debugging, and production support investigations.

• Delivered and maintained third-party platform integrations that synchronized structured meeting outputs, improving downstream usability and data consistency.

• Partnered with product to iterate quickly on customer-facing workflow UX, balancing rapid shipping with reliability and maintainability.

• Built and scaled an AI-assisted ingestion pipeline (classification, splitting, extraction) converting unstructured PDFs/faxes into structured, workflow-ready data.

• Integrated LLM/AI APIs into extraction and validation steps to increase automation coverage and reduce manual review, with clear fallbacks for uncertain cases.

• Migrated long-running ingestion and automation to Temporal, improving reliability with durable execution, retries/timeouts, and safer scaling under high volume.

• Owned features end-to-end across UI, backend services, and infrastructure—shipping fast while maintaining clean handoffs between review screens and automated workflows.

• Strengthened observability and operational resilience (failure handling, edge-case recovery, performance tuning) to keep production workflows diagnosable and stable.

• Worked directly with customer technical stakeholders to refine requirements, validate behavior, and deliver low-risk rollouts.