Current Position
Software Engineer, Infrastructure at Pay-i
Bellevue, WA | Feb 2025 — Present
Kubernetes, Helm, AWS, Azure, Terraform, Bicep, CloudFormation, Docker, C#, Dotnet
Architected and executed end-to-end migration of Azure App Services to multi-cloud Kubernetes architecture (AKS and EKS), utilizing Terraform, Helm, and Flux, enabling Bring Your Own Cloud (BYOC) enterprise customer deployments.
Engineered and supported single-tenancy deployments via Azure Managed Applications and Terraform-provisioned AWS environments, leveraging cross-account IAM policies to manage infrastructure and application lifecycles across isolated client accounts.
Implemented application-wide OpenTelemetry instrumentation (traces, metrics, logs) to meet enterprise compliance. Built out the core monitoring and security infrastructure, creating Grafana dashboards, alerting rules, and cluster RBAC policies.
Managed the deployment and scaling infrastructure for a high-throughput CDC pipeline (PostgreSQL, ClickHouse, PeerDB, Temporal), reducing compute costs by aggressively right-sizing Kubernetes nodes across our entire stack.
Previous Positions
Software Engineer at Ambassador Software
Seattle, WA | June 2021 — Feb 2025
Python, Django, PostgreSQL, Redis, Celery, Docker, AWS, GCP, JavaScript, React, BigQuery
Built the core execution engine for a no-code workflow product (Python/Celery), dynamically parsing JSON API payloads into boolean logic trees to evaluate customer-configured data rules
Increased system uptime from 95% to 99.95% and reduced average response latency by 60% through aggressive database query optimization, asynchronous job refactoring, and query caching.
Migrated the public-facing API from Node.js to Django, writing an extensive suite of unit tests to guarantee functional parity and ensure a zero-regression rollout.
Built an automated analytics data warehouse utilizing AWS RDS, S3, BigQuery, and Google Apps Script to power large-scale customer data exports and accelerate internal business insights.
Data Science Intern at ContextLink
Seattle, WA (Remote) | September 2020 — May 2021
Python, Pulumi, AWS, Pandas, NumPy, scikit-learn
Built an automated data preprocessing workflow using AWS S3 and Lambda to trigger an ordinal encoder for categorical features, improving data consistency and training reliability.
Developed Python utilities for data transformation and feature encoding (Pandas, NumPy, scikit-learn) while learning cloud integration patterns with Pulumi and AWS services.