As a Senior Software Engineer and Technical Product Owner on the Personalization Team, I lead the design, development, and deployment of machine learning-driven personalization solutions. My responsibilities span technical leadership, product strategy, and hands-on engineering. I work extensively with Python, Django, PySpark, Airflow, EMR, and Terraform to build and maintain key personalization models, including Customer Lifetime Value (CLV), Channel Affinity, Expected Date of Next Order, Expected Date of Next Cross Sell, Next Best Product, and Personalized Send Time.

I developed and continue to maintain the RFM (Recency, Frequency, Monetary) feature used, currently the leading selling feature in Klaviyo's KDP and MA offering.I led the development of both the Expected Date of Next Cross Sell and Next Best Product models, driving end-to-end implementation from model design to production deployment. I am currently leading the development of a Personalized Send Time Optimization system to improve customer engagement through precise timing of communications. In my TPO role, I help define the team's timeline and technical requirements, align cross-functional priorities, and ensure our personalization products deliver measurable business value.

As a Software Engineer, I contributed to the development of internal tools and data integrations that supported advertising and inventory optimization for products sold on Amazon.com. I designed and built manual advertising campaign controls, enabling more granular campaign management. I also led the development of automated campaign controls that dynamically responded to stock status, improving advertising efficiency and reducing waste.

In addition, I integrated Inventory Forecast data into the broader data pipeline and built an asynchronous process to upload this data reliably and at scale, improving operational visibility and planning.

As a Software Engineer at Chewy, I was responsible for designing, developing, and deploying several core backend services that supported personalization, pricing, and promotions. I led service architecture efforts, wrote production-grade code, conducted code reviews, and collaborated with platform engineering to ensure scalability and high availability across systems.

Segment Membership Service:

I designed and built this RESTful service from the ground up to allow internal services to quickly verify customer or product membership in defined segments. This enabled use cases such as promotion eligibility checks and personalized recommendations. The service was deployed to AWS and used actively in production.

Promotion Engine:

I led the design and code reviews for the Cart Validation Engine, which determined applicable promotions for customer carts and managed promotion codes. This service was also deployed to AWS and used in production environments.

Multi-Region / Multi-Availability Strategy:

I partnered with platform engineering to migrate services to a multi-region architecture for greater fault tolerance. I developed recovery strategies for service failures (ECS, Lambda, etc.) and implemented data synchronization plans across regions. This strategy was successfully deployed to production.

Pricing Engine:

I led the architectural design for Chewy’s next-generation pricing engine, a suite of services responsible for determining real-time product pricing. I authored development, testing, and execution strategies, contributed to service implementation, and led code review and standardization efforts. This project was in active development during my tenure.

As a Software Engineer II at Chewy, I focused on building scalable, intuitive internal platforms that empowered non-technical stakeholders to manage promotions and customer segmentation. I played a key role in both backend service design and frontend integration, contributing to projects that were critical to Chewy’s personalization and marketing infrastructure.

Segment Management Service:

I led design discussions and was responsible for building the SQL statement builder engine and APIs for this web-based platform. The service allowed internal users to define customer segments using SQL-like logic via an intuitive UI and push those segments to downstream systems (e.g., Segment Membership Service) and external platforms like Facebook. Originally deployed on-prem, the service was later migrated to AWS (Nebula 2) and remained in active production use.

Promotion Authoring Platform:

I led the design and implementation of the Cart Validation Model used to determine applicable promotions for customer carts. I developed the engine that converted legacy Java-based promotions into the new validation model, and created the migration scripts to transition all existing promotions into the updated system. This web service empowered business users to create and manage promotions via a React-based UI and was successfully deployed to production, later migrated to AWS infrastructure.

I worked at Amazon Robotics as an SDE on the Movement Services team. On the team, I was the lead engineer working for the the service that manages maintenance activities at Amazon's fulfillment centers. The service utilizes many of AWS's tools such as SWF, Dynamo DB, and S3 for managing, scheduling, and storing the various activities occurring on the floors of the FCs.