OpenAI album artwork

OpenAI

Member of Technical Staff

Mar 2026 – Present · 7 tracks

From fragmented sources to usable intelligence.

End-to-end engineering for an AI-powered intelligence platform—from durable data pipelines and evidence-grounded analysis to the workspace analysts use every day.

Selected work

  1. End-to-end platform ownership

    Own end-to-end engineering for an AI-powered intelligence platform spanning Python/FastAPI services, Temporal workflows, versioned data models, APIs, access control, TypeScript/Next.js applications, and operational tooling.

  2. A durable processing pipeline

    Re-architected a failure-prone processing system into a durable, multi-source pipeline with deduplicated collection, artifact-backed payloads, idempotent storage, bounded evidence processing, transactional writes, and asynchronous alert delivery.

  3. Production migrations with continuity

    Led staged production migrations through two generations of workflow and data architecture while preserving user continuity; added feature-gated rollouts, backfills, reconciliation tooling, integration tests, telemetry, and health monitoring.

  4. Evidence-grounded intelligence

    Built an evidence-grounded intelligence layer combining LLM and research agents, source-linked narrative histories, semantic continuity across time, scheduled generation, historical backfills, executive summaries, trend analysis, and evidence drilldowns.

  5. The analyst workspace

    Shipped the core analyst workspace, including feed creation and discovery, provider configuration, source exploration, version history, AI-assisted prompt authoring, feedback review, analytics, and role-based authorization.

  6. Data access for downstream teams

    Delivered filterable, paginated source-data APIs and agent-accessible query tooling that enabled other teams to programmatically consume intelligence data for downstream analysis and modeling.

  7. Operational ownership

    Partnered directly with analysts, investigators, product leaders, and data providers; translated operational needs into product capabilities and led incident response, stakeholder onboarding, and production support.