My Experience @
Amgen
Amgen is a leading biotechnology company whose mission is to serve patients. I am currently working as a Software Engineer (Tech Lead), architecting and delivering a mission-critical executive notification platform powering CEO/CXO workflows.
Python
FastAPI
PostgreSQL
Redis
AWS
Kubernetes
Docker
React
Grafana
OpenAI
What I did at Amgen
System Architecture & Design
Architected and delivered a mission-critical executive notification platform powering CEO/CXO workflows with near real-time delivery guarantees.
Migrated legacy cron-based polling architecture to an event-driven system, significantly reducing latency and enabling scalable real-time notifications.
Designed v2 service architecture across multiple repositories using Low-Level Design (LLD) principles and design patterns to improve modularity and maintainability.
Backend Development & Optimization
Eliminated 2000+ scheduled cron jobs by implementing batching and job deduplication strategies, improving compute efficiency and operational reliability.
Refactored core notification pipelines and configuration systems, reducing feature delivery effort from 8 story points to 3.
Introduced AI-assisted refactoring workflows to accelerate modernization across repositories while maintaining production safety.
Engineering Leadership & Process
Led a team of 3 engineers, driving sprint planning, architecture discussions, and production delivery of scalable backend modules.
Established engineering best practices and code review standards, improving consistency and development velocity across teams.
AI at Amgen
How I used AI in my workflow
LLMs for refactoring
Used LLMs to generate migration plans for legacy codebases — fed in old patterns, got back refactored versions with explanations. Reviewed and applied selectively rather than blindly accepting output.
AI-assisted code review
Ran diffs through LLMs before human review to catch edge cases, naming inconsistencies, and missing error handling. Reduced back-and-forth in review cycles.
Prompt-driven architecture exploration
Used AI as a sounding board when designing the event-driven migration — prompted with constraints, compared tradeoffs, then validated decisions with the team.
Boilerplate and test generation
Automated repetitive scaffolding (API route stubs, schema definitions, test fixtures) using LLMs, freeing time for higher-leverage work.