Backend Engineer | Infrastructure Optimizer | AI Systems Architect
Building scalable platforms and developer tooling on AWS. I architect AI-powered systems adopted by 50+ managers, optimize infrastructure (81% cost reduction), and ship production code that matters.
I'm a Backend Engineer with 2+ years of production experience architecting AI-powered platforms and developer tooling at DevDynamics. I've grown from intern to SDE 2, shipping features used by thousands of engineering teams.
My expertise spans:
- Multi-agent LLM systems with LangGraph and FastAPI
- Microservices architecture and event-driven systems
- Database performance optimization at scale (60M+ rows)
- Cloud infrastructure optimization (81% cost reduction on AWS)
- Full-stack backend development with NestJS, Spring Boot, Express
I'm passionate about solving hard engineering problems—whether it's building AI copilots, mentoring junior engineers, or cutting infrastructure costs through targeted optimization.
- Microservices & Event-Driven Architecture
- Query Optimization & Performance Tuning
- Distributed Systems & Concurrency Control
- AI/LLM Systems & RAG
- ETL Pipelines & CDC
- AST Analysis
Building an AI-powered analytics copilot with LangGraph supervisor/collector agents and FastAPI streaming.
- Impact: 50+ manager adoption, 100+ active chat sessions
- Tech: FastAPI, LangGraph, PostgreSQL, AWS Lambda, SSE
- Key Features: Multi-metric aggregation, parallel data fetch, streaming responses
End-to-end AI platform for intelligent code review built in TypeScript with ephemeral AWS infrastructure.
- Architecture: ECS, SQS, Lambda, S3 with zero-persistence code handling
- Collaboration: Built directly with CTO from prototype to production
- Security: Ephemeral execution ensures client code is never persisted
Reduced AWS infrastructure spend from ~$4,200 to ~$800/month through targeted optimization.
- Optimizations: Fargate → EC2, ECS autoscaling, load balancer consolidation
- Database: Cold-storage migration, replica removal, instance right-sizing
- Result: 81% reduction while maintaining reliability
Diagnosed and resolved critical production issues in a massive PostgreSQL table.
- Performance: Worst-case query from >30s to <500ms, API latency 7–10s to 1–2s
- Techniques: CTE rewrites, index-friendly query restructuring, 200+ query variants optimized
- Impact: Fixed data accuracy for international customers
I write about cloud optimization, AI systems, database performance, and backend engineering on my Hashnode Blog
Recent topics:
- Aurora RDS Optimization: 84% Cost Reduction
- Query Optimization Techniques for Large Datasets
- Building AI-Powered Platforms with LLMs
- Infrastructure Cost Optimization Strategies
- Portfolio: shantanubadmanji.com
- Blog: shantanubadmanji.hashnode.dev
- LinkedIn: linkedin.com/in/shantanu-badmanji
- Email: shantanubadmanji1912@gmail.com
- Discussing backend architecture and infrastructure optimization
- Building AI-powered systems and LLM applications
- Database performance tuning and optimization
- Mentoring engineers and knowledge sharing
- Collaborative projects on scalable systems
Let's build something amazing together! 🚀
Made with ❤️ by Shantanu | DevDynamics