๐ข Currently: Architecting enterprise systems at John Deere ๐
๐ผ Previously: Built mission-critical platforms at Morgan Stanley, Deloitte, TransUnion
โก Experience: 10+ years crafting distributed systems that power millions of transactions
๐จ I specialize in:
- ๐๏ธ Designing fault-tolerant architectures that scale
- ๐ Leading technical initiatives from concept to production
- ๐จโ๐ซ Mentoring engineers and building high-performing teams
- โก Optimizing systems for performance and reliability
๐ฅ My superpower? Turning complex technical challenges into elegant, scalable solutions
๐ My impact? 10+ engineers mentored, 40% faster onboarding, 30% fewer production incidents
๐ก "I don't just write codeโI architect experiences that scale"
๐๏ธ Architect large-scale distributed systems handling 8k+ requests/sec
โก Optimize performance - reduced latency, improved throughput, scaled infrastructure
๐จโ๐ซ Mentor engineers - structured programs, code reviews, technical growth
๐จ Design resilient microservices with fault tolerance and high availability
๐ Drive technical roadmaps and architectural decisions across organizations
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๐ฆ E-Trade Stockplan Modernization - Morgan Stanley Trading Platform
The Challenge: Legacy AngularJS platform struggling with technical debt and SEC compliance requirements
My Role: Technical Lead & System Architect
What I Built:
- ๐ง Frontend Modernization: Spearheaded complete AngularJS โ React migration across stockplan trading platform
- ๐ Event Architecture: Designed real-time event-driven system using Kafka for compliance event propagation
- ๐ Compliance Engine: Implemented SEC 10b5-1 regulatory compliance framework ensuring trade restriction enforcement
- ๐ Performance Boost: Optimized rendering and state management reducing page load times by 27%
- ๐ฏ System Observability: Integrated distributed tracing for real-time monitoring and debugging
Tech Stack: React Kafka Spring Boot TypeScript Redux REST APIs
Impact:
โ
40% reduction in technical debt
โ
Zero compliance violations post-launch
โ
Improved developer velocity by 35%
โ
Enhanced user experience with modern UI/UX
๐ BFF & API Standardization Platform - Morgan Stanley Enterprise Architecture
The Challenge: Multiple trading platforms with inconsistent API contracts causing code duplication and maintenance overhead
My Role: Principal Architect & Technical Lead
What I Built:
- ๐๏ธ Backend-for-Frontend Layer: Architected centralized BFF service standardizing REST API contracts across 3+ platforms
- ๐ Reusable Patterns: Created library of shared API patterns, DTOs, and validation logic adopted organization-wide
- ๐ Scalability Design: Implemented circuit breakers, retry mechanisms, and rate limiting for 8k+ concurrent requests/sec
- ๐ API Gateway: Designed unified gateway handling authentication, authorization, and request routing
- ๐ฏ Documentation: Established OpenAPI specifications and auto-generated API documentation
Tech Stack: Spring Boot Spring Cloud Redis gRPC OpenAPI Microservices
Impact:
โ
25% reduction in code duplication
โ
Consistent API experience across all platforms
โ
3x faster feature development for new endpoints
โ
Improved API response times by 15%
โ๏ธ AWS Serverless Data Processing Ecosystem - Deloitte Cloud Solutions
The Challenge: High infrastructure costs and scaling limitations with traditional server-based architecture
My Role: Cloud Architect & Lead Developer
What I Built:
- โก Serverless Pipeline: Designed end-to-end data processing platform using Lambda, API Gateway, SQS, and S3
- ๐ Event Processing: Built event-driven workflows processing 10M+ events daily with automatic scaling
- ๐พ Data Lake: Architected S3-based data lake with lifecycle policies and cost optimization strategies
- ๐ Security Framework: Implemented IAM roles, encryption at rest/transit, and VPC isolation
- ๐ Monitoring Suite: Deployed CloudWatch dashboards, alarms, and distributed tracing for system health
- ๐ฏ CI/CD Pipeline: Automated deployment using AWS SAM and CloudFormation for infrastructure-as-code
Tech Stack: AWS Lambda API Gateway SQS S3 DynamoDB CloudWatch Python Node.js
Impact:
โ
35% reduction in infrastructure costs
โ
99.95% uptime SLA achievement
โ
Zero-downtime deployments
โ
Auto-scaling handling 10x traffic spikes
โ
Sub-100ms API response times
๐ Legacy Billing System Modernization - TransUnion Financial Platform
The Challenge: Mission-critical monolithic batch application processing 500k+ daily transactions with scalability bottlenecks
My Role: Senior Engineer & Migration Lead
What I Built:
- ๐๏ธ Microservices Architecture: Decomposed monolith into 12+ independent microservices with domain-driven design
- ๐ Batch Processing: Engineered high-performance jobs handling 50M+ records daily using Spring Batch and multi-threading
- ๐ Kafka Integration: Designed fault-tolerant message handling for reliable event delivery across services
- ๐พ Database Optimization: Implemented connection pooling, caching, and query optimization reducing latency by 30%
- ๐ REST API Layer: Built secure REST API ecosystem using Spring Security and JWT authentication
- ๐ฏ Angular UI: Created modern Angular 4 interface replacing legacy UI with improved UX
- ๐ง Workflow Automation: Orchestrated batch jobs using AutoSYS scheduler with custom Shell Scripts
Tech Stack: Java Spring Batch Kafka Angular 4 PostgreSQL REST APIs AutoSYS
Impact:
โ
50% faster deployment cycles
โ
Independent service scaling enabled
โ
30% improvement in query performance
โ
99.9% batch job success rate
โ
Improved system maintainability and fault isolation
โ
Regulatory compliance for financial transactions
๐ฅ๏ธ Desktop Services Infrastructure - John Deere Enterprise Platform
The Challenge: Global fleet management requiring enterprise-grade device management at massive scale
My Role: Staff Engineer & Infrastructure Architect
What I'm Building:
- ๐ง Cloud-Native Architecture: Architecting desktop services leveraging Microsoft Intune and Azure cloud ecosystem
- ๐ Global Scale: Designing fault-tolerant systems for worldwide fleet management and device orchestration
- ๐ฏ Performance Engineering: Optimizing system performance for enterprise-grade solutions handling millions of devices
- ๐ Security Standards: Establishing architectural standards for secure cloud-native Microsoft integrations
- ๐ Distributed Systems: Leading technical investigations for large-scale distributed desktop services
Tech Stack: Microsoft Intune Azure Cloud Distributed Systems Enterprise Architecture
Impact (In Progress):
๐ Architecting next-gen enterprise device management
๐ Establishing cloud-native best practices
๐ Driving system design for global scale
- ๐ Deep diving into Distributed Systems Patterns
- ๐ฏ Contributing to Apache Kafka ecosystem
- โธ๏ธ Mastering Kubernetes orchestration
- ๐๏ธ Advanced System Design patterns
- ๐ค Platform Engineering best practices
I'm always excited to discuss:
- ๐๏ธ System architecture and design patterns
- โก Performance optimization techniques
- ๐ Scalability challenges
- ๐จโ๐ซ Engineering leadership and mentorship
- ๐ก Open source contributions
๐ซ Reach me at: [email protected]
๐ LinkedIn: linkedin.com/in/abhijeets93
๐ Location: Bengaluru, India ๐ฎ๐ณ
โญ๏ธ From selvester69 | Made with ๐ and โ
