AM

Selected projects

Data & AI architecture projects.

Work across open-source integrations, agent runtime orchestration and data platform design. The common thread is simple: make the architecture explicit, test the difficult path and leave behind something reusable.

Current work

From proof to working path.

01

Open source · Python

Agentic Airflow Demo

A working Apache Airflow proof of concept that sends failed DAG context to a containerized AI agent, produces a diagnosis, opens a draft GitHub pull request and posts a concise summary to Slack.

Why it matters

The same troubleshooting loop runs across AWS Bedrock AgentCore, Google Vertex AI Agent Engine and Microsoft Azure AI Foundry Agents.

  • Apache Airflow
  • AI agents
  • AWS
  • Google Cloud
  • Azure
View repositoryRead the walkthrough
02

Open source · Apache Airflow

Cross-cloud agent lifecycle orchestration

Native Airflow operators for creating, invoking, updating and deleting managed AI agent runtimes across three cloud providers.

Why it matters

Three provider contributions were merged upstream, making the lifecycle operations available from Airflow DAGs.

  • Provider development
  • Agent runtimes
  • Multi-cloud
See contribution record
03

Open source · Apache Magpie

Evidence-grounded AI code review

Apache Magpie is an agent-assisted maintainership framework for Apache projects. This contribution made its PR-management review skill prove dependency findings against every mandatory direct and transitive constraint while following each adopter repository's policy.

Why it matters

Merged as PR #1048 with five dependency-compatibility regressions. Open follow-up PR #1060 adds an empty-intersection case and grades every suggested remediation against adopter policy.

  • Apache Magpie
  • Agent skills
  • Code review
  • Dependency analysis
View merged pull requestView follow-up PR #1060
04

Open source · Apache Airflow

AWS DMS task lifecycle operations

Merged Airflow operators for modifying AWS DMS replication tasks and reloading selected target tables as explicit DAG operations.

Why it matters

The reload operator supports synchronous and deferrable waits, configurable retry behavior and templated arguments, and was validated end-to-end against AWS alongside 131 passing unit tests.

  • Apache Airflow
  • AWS DMS
  • Deferrable operators
  • Provider development
Reload tables PR #70569Modify task PR #67524
05

In progress · Apache Airflow

Oracle Cloud Infrastructure for Apache Airflow

Foundational OCI support for the Oracle provider: a native Airflow connection and reusable hooks for OCI Generative AI Hosted Applications and Hosted Deployments.

Why it matters

The open contribution adds four authentication modes, optional OCI SDK packaging, connection testing and native-client hooks that establish the base for follow-up lifecycle operators.

  • Apache Airflow
  • Oracle Cloud Infrastructure
  • Generative AI
  • Provider development
View open pull request
06

In progress · Product engineering

Morgan DataHub

A multi-tenant data platform proof of concept packaged as a reusable container, with tenant configuration and image versions managed as infrastructure as code.

Why it matters

The current design favors isolated tenant runtimes, reproducible deployments and explicit promotion of container image versions.

  • Docker
  • Terraform
  • AWS
  • Multi-tenant
07

Architecture · Published

Modern Data & AI Platform

A reference architecture connecting operational data capture, transformation, governance and observability with an AI-ready serving layer.

Why it matters

The design treats reliability, metadata and security as part of the platform instead of adding them after the first workloads arrive.

  • Data platform
  • AWS
  • Governance
  • AI
Read the architecture