Selected work

Engineering work and focus areas

A generalized, privacy-safe view of the kind of work I lead and build. Details are kept high-level by design — the intent is to show scope and approach, not internal specifics.

  1. 01

    Customer Engineering and Support Systems

    Built and led teams around customer-facing engineering workflows, escalation handling, integration support, and operational tooling.

    Focused on turning reactive support into a durable engineering function: clearer escalation paths, better integration support, and tooling that reduced repetitive operational load.

  2. 02

    Platform, Data, and Infrastructure

    Led modernization efforts across high-volume event data, warehouse and reporting systems, analytics workflows, and operational visibility.

    Prioritized reliability and observability as first-class concerns — treating data infrastructure and reporting as products the business depends on rather than back-office plumbing.

  3. 03

    Security and Compliance

    Owned or supported engineering-side security, audit readiness, process improvements, and cross-functional risk reduction.

    Worked across engineering and adjacent functions to make security and compliance a steady operating rhythm rather than a periodic scramble.

  4. 04

    AI-assisted Engineering Operations

    Designed practical workflows using AI coding tools, internal agents, structured prompts, and automation to reduce repetitive engineering work.

    Emphasis on leverage over novelty: workflows that hold up in daily use, with guardrails, review, and clear ownership rather than one-off demos.

  5. 05

    Forward Deployed Engineering

    Independent product and workflow experiments in agentic systems that execute real business operations, rather than add conversational UI to existing software.

    LeaseLab is the primary proving ground: an event-sourced property-management system where agents observe rent and maintenance state, detect genuine operational exceptions, act within explicit human-set boundaries, and hand physical-world steps back to a landlord before resuming ownership of the workflow. Also testing whether a resolved exception — not a seat, a token, or a feature used — is a more honest unit of software value than the usual SaaS metrics.

  6. 06

    Homelab and Infrastructure

    Maintains a private infrastructure environment across networking, storage, virtualization, Kubernetes, monitoring, and automation.

    A hands-on environment for staying close to the systems layer — networking, storage, virtualization, and automation — that informs how I lead infrastructure work.