Senior Software Development Engineer
Tech Lead for Agentic, ML Ops, and Data Platform
Amazon Advertising Partner Tech Org
- Architected and delivered Partner Knowledge Base; wrote doc, spun up project, aligned across 6 different tech and product teams, got executive sponsorship, and created a durable pattern for knowledge sharing with Agents across the Partner Tech org. Utilizes MCP as the interface to work with any agent and the harness is Strands on AWS AgentCore.
- Rearchitected MLOps tooling & infrastructure, cutting time to production from 3 months to 2 weeks and delivered 12 models in 6 months vs the 1 model in 2 years prior. Made models CI/CD raising the quality bar and preventing regressions from sneaking in. Trained up scientists on new workflow, both speeding up and making their work more reliable. Scales across thousands of machines with AWS Batch allowing us to run previously yearly models on a weekly basis, all completely serverless saving money over the previous approach. Minimal maintenance despite the scale; we see less than 1 failure per week.
- Took on the ML Ops project solo after it had sat idle for a while. Ramped it up within a month, showed turnaround, and spun up a team, first with one other engineer. Demonstrated success and showed how a focused platform team could improve velocity for the org, making the pitch not for a short lived tiger team but our current AI/ML/Data SDE team. A year later we're now a team of seven. In the founding phases, I led team as both a tech lead and manager until we could hire a one, interfacing with product and leadership.
- Designed and built a generic Spark data precompute pipeline which processes over 1 PB of data each month and has influenced more than $3B in advertiser spend in 5 years. Handles arbitrary queries, transforms, indexes, archival, and federated ownership of datasets.
- Mentor engineers, align business, science, and engineering teams across orgs and lead the team in code changes, designs, and reviews.
