Senior Technical Program Manager Nashville, TN
I bring business teams and engineers together to take ideas into production.
Now at Amazon, including earlier work at AWS. Previously Deloitte and PwC.
I owned the architecture of a shared data platform. I wrote its pipelines and managed delivery. Colleagues use it for operational reports and leadership dashboards that track progress against team goals.
I built an agent that shows application owners what to fix before they send a review back. I shipped a package that makes those findings available in coding assistants.
Engineering
I connected the agent to review data and policy guidance. Application owners and reviewers see the same findings.
Adoption
I defined requirements with engineers and legal counsel. I led evaluation and release. I now work with other teams to use the system’s outputs in their own workflows.
The first version asked a model to handle the whole review. Its answers varied between runs.
I moved explicit requirements into repeatable checks and kept AI for interpretation. Reviewers make the final decisions.
I built Nashville School Navigator to turn a family’s address and child’s grade into a school shortlist shaped by their priorities. It includes admissions and school-performance information, with gaps in cost data called out.
A working prototype, not yet used by families.
How it works
I use tools to retrieve school facts and Claude to explain the options. Checks compare school names and tuition fields with the source data.
I wrote the prototype in Python with LangGraph. A geocoder locates the address for district zone lookup. Other tools retrieve state school-performance data and apply scholarship rules.
Across ten test families, my checks found no invented school names or tuition figures. The repository includes the evaluations and recorded runs.
I automated weekly finance reporting with tools the team still uses after my move to another role.
For a separate month-end productivity report, I automated the queries that filled the file. Leaders could use one view of actuals against plan to investigate variances without first reconciling the figures.
My contribution
I owned the reporting roadmap. I wrote SQL pipelines for dashboards and added anomaly detection. I guided engineers through their analyses and code reviews.
Projects were reaching leadership reviews without a clear calculation behind their savings claims. I required owners to document that calculation alongside the estimate.
My contribution
I tested productivity gains against normal variation before estimating financial benefits.
I’ve worked as an accountant, a cybersecurity consultant, a finance lead, and a data engineer. Each gave me a different way to test an idea.
My written proposal for automation didn’t win support. A prototype I built and tested with users did.
I sat with specialists to document their review criteria. They helped shape the checks and championed adoption.
I worked in the kitchen and dining room at family-owned restaurants—a steakhouse and an Italian/Greek restaurant.
Oak Ridge National Laboratory, HCA in Nashville, DHG in Atlanta, and PwC in Atlanta.
At PwC and Deloitte, I worked in IT risk and cybersecurity.
At Amazon, including AWS, my work moved from operations finance to data engineering and AI.
Credentials
Books I’ve loved and resources I use.
I’m an Amazon Machine Learning University Champion with six course completion certificates.