Full stack software engineer currently working on Developer Experience at HubSpot to create scalable AI coding infrastructure to accelerate and empower engineers. Previously, I worked on the Edge team, developing highly resilient load balancing infrastructure capable of handling millions of requests per second.
Led development on internal AI background agent execution platform, allowing engineers to trigger background coding agents from GitHub and at scale using internal code migration tools. AI agents perform automatic code reviews (thousands/week), automatic code implementation (hundreds of PRs/week), and are deeply integrated with HubSpot developer tooling. Feature-set comparable with managed Microsoft GitHub Copilot coding agent at a fraction of the cost. Used Java, Docker, and Kubernetes.
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Deployed AI coding agents (Claude, Cursor, Copilot) for all HubSpot engineers, raising AI adoption to 100%. Developed internal MCP server, tools, and rules to give agents the context required to effectively work on HubSpot code. Used Python and FastMCP.
Managed critical load balancing infrastructure which processes millions of requests/second, developing scaling automation, monitoring tools, and triaging production issues to ensure the reliability of the HubSpot product. Used Kubernetes, Envoy, Nginx, Cloudflare Workers, and Grafana/Prometheus/PromQL for observability.
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Migrated thousands of Kubernetes resources representing critical networking infrastructure to infrastructure as code (IaC), allowing for peer review of changes and reducing the time to expand to new AWS regions from months to just a few days. Used Kubernetes, Python, and Jsonnet.
Created developer CLI to automate AWS Lambda deployments, reducing iteration time by >90% from a 30+ minute manual process to just a few minutes. Used TypeScript and Ink.
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Implemented redesigned course catalog page, developing frontend and backend components to meet designer specifications. Used TypeScript, React, DynamoDB, and AWS Lambda.
Implemented auto-merging dependency updates across Wayfair, resulting in 10,000+ auto-merged pull requests and saving hundreds of engineer hours. Used Python, Renovate, and GitHub.
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Led API redesign for internal development platform (IDP) backend, enabling Wayfair leaders to model problem domains, service ownership, and report costs for decoupled microservices. Led optimization efforts, allowing team to meet uptime SLAs and reducing endpoint latency by >95%. Used Python, FastAPI, Backstage, SQL Server, Buildkite, Docker, and Kubernetes.
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Mentored team in Python best-practices and scalability, establishing and leading weekly design meetings. Encouraged test-driven development, increasing test coverage in our services to >90%.
Implemented caching for search endpoint of configuration service deployed across Chewy for more than 10x speed-up. Used Python, AWS Lambda, DynamoDB, ALB, Elasticache, and Terraform.
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Created and ran load tests for configuration service. Used Scala and Gatling/Frontline.
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Automated RDS Aurora PostgreSQL database deployments. Used Golang, Jenkins, and Docker.
