My Experience @
Amgen
Amgen is a leading biotechnology company whose mission is to serve patients. The company supports its staff through numerous internal projects; currently, I am contributing to the notifications team, which is responsible for delivering real-time updates on key organizational metrics and initiatives to executive leadership — enabling informed, data-driven decision-making across the company.
Python
Kubernetes
Docker
React
HTML
CSS
PostgreSQL
Grafana
OpenAI
DynamoDB
SQS
Lambda
At Amgen, I have...
System Design & Architecture
1. Refactored the notification system architecture to simplify data flow and configuration management, reducing feature delivery effort from 8 to 3 story points.
2. Developed the v2 codebase across multiple repositories using Low-Level Design (LLD) principles and design patterns, improving maintainability and modularity.
3. Migrated from cron-based polling to an event-driven architecture, enabling near real-time notification delivery and reducing latency.
4. Introduced batching logic and job deduplication, reducing over 2000 redundant cron jobs and improving compute efficiency.
5. Initiated and led the transition to event-based triggers, aligning with microservice architecture principles and reducing dependency on scheduled jobs.
Engineering Leadership
1. Led a team of 3–4 engineers, managing sprint planning, architecture discussions, and the delivery of scalable notification modules.
2. Collaborated with DevOps and platform teams to ensure alignment with CI/CD, observability, and deployment best practices.
3. Enhanced traceability and auditing through centralized logging and observability integration, improving root-cause analysis and monitoring.
4. Advocated for maintainable coding practices and effective design reviews to ensure high-quality, production-ready code.
Optimization & Observability
1. Improved system observability by integrating Grafana dashboards and centralized logging pipelines.
2. Enhanced root-cause analysis and production visibility through consistent use of structured logs and monitoring alerts.
3. Collaborated cross-functionally to align performance optimizations with Kubernetes deployments and scaling configurations.