Built and scaled cloud services for IBM's quantum computing platform, progressing from owning mission-critical microservices to delivering platform infrastructure for GA and FedRAMP readiness. Implemented CI/CD across gateway and frontline services with automated testing and security scanning that became the foundation for our compliance pathway. Delivered key features through the IBM Cloud replatforming, including instance workloads (jobs/sessions) and the Admin User Analytics migration, and supported the move to private endpoints. Drove reliability practices by authoring disaster recovery plans, establishing SRE patterns, and handling incidents as part of the on-call rotation. Enabled multi-region compliance and data classification/migration efforts across services and data boundaries. Owned the Interim Qiskit Runtime service that carried production workloads during the transition of services, including Bring-Your-Own-Bucket and execution-time prediction features. Worked across Go and TypeScript services on Kubernetes with OpenTelemetry and Prometheus, PostgreSQL and MongoDB data layers, and NATS messaging; the role centered on distributed systems and platform reliability at scale.

Selected Highlights:

• Implemented CI/CD for core gateway and frontline services; major step toward GA readiness

• Delivered IBM Cloud replatforming features: instance workloads and Admin User Analytics

• Implemented SAST/DAST/dependency vulnerability scans and supported resolution

• Enabled multi-region compliance across services; supported data privacy measures

• Authored disaster recovery plans, established SRE patterns, and handled incidents on-call

• Owned Interim Qiskit Runtime service carrying production workloads during service migration

• Awarded CEO-signed recognition for contributions to Quantum Premium revenue milestone

Tech Stack: Go, TypeScript, Kubernetes, Docker, PostgreSQL, MongoDB, Node.js, NestJS, NATS, OpenTelemetry, Prometheus, Grafana, ArgoCD, Helm, IBM Cloud

I write clean, well-architected software to deliver Qiskit and IBM’s Quantum services.

Developed a cross-platform mobile app for event coordination in tight iteration cycles with company founders. Built the complete feature set: real-time collaborative markdown notes, shared media, expense tracking with Venmo integration, push notifications, Maps-based location, and OAuth authentication. Delivered through TestFlight with rapid feedback incorporation. The contract ended when I transitioned to full-time work at IBM. The project reinforced mobile engineering patterns—state management across network transitions and third-party SDK integration—while building skills in translating product requirements directly from founders into technical implementation.

Selected Highlights:

• Built real-time event coordination with collaborative notes and media sharing

• Integrated OAuth (multiple providers), Venmo payments, Maps, and push notifications

• Delivered through rapid TestFlight iteration cycles with founder feedback

• Handled offline behavior and state synchronization across clients

• Worked directly with founders in tight iteration cycles and rapid releases

Tech Stack: React Native, Node.js, iOS

Wrote and tested software as a part of the IBM Quantum Software team.

Built a predictive analytics platform for football coaching, integrating ML models with real-time game interfaces. The system extracted structured data from HUDL (building custom scrapers since no API existed), ran automated data cleaning and feature engineering, trained TensorFlow models with hyperparameter optimization, and served predictions through a web interface. The platform supported selecting game data for training, deploying custom models, and using them during live games via a real-time interface. The technical challenge was data engineering—handling inconsistent inputs and building reproducible ML workflows. Stopped the project after determining model accuracy couldn't reliably beat human intuition with available data. The experience built skills in ML infrastructure, data pipeline design, and the discipline to evaluate technical viability objectively.

Selected Highlights:

• Built custom HUDL data extraction pipeline (no official API available)

• Implemented automated data cleaning and feature engineering workflows

• Designed multi-model training system with Optuna hyperparameter optimization

• Created real-time interface with live TensorFlow.js inference

• Architected microservices: data parser, ML training, API gateway, frontend

• Deployed full Docker-based infrastructure for ML pipeline

Tech Stack: Python, TensorFlow, Keras, Optuna, Scikit-Learn, Pandas, Node.js, React, TensorFlow.js, Docker