Senior Software Engineer • Technical Lead • Distributed Systems Architect
Building production-grade backend systems that scale, fail gracefully, and evolve safely. Specialized in distributed systems, event-driven architectures, and AI-integrated backends.
- 13+ years designing and building scalable backend systems for enterprise and SaaS platforms
- Team Leadership: Led engineering teams of 7–10 engineers across distributed systems projects
- Expertise: Microservices, event-driven architectures, AI/LLM integration, real-time systems, and cloud infrastructure
- Global Experience: Worked with international teams including Japanese SaaS companies and multinational enterprises
I optimize for production reliability, not just functionality.
My Focus:
- ✅ Systems that scale under extreme pressure without degradation
- ✅ Architectures that fail gracefully with proper fallback mechanisms
- ✅ Codebases that empower teams to evolve and refactor safely
Core Belief: Most production failures stem from poor architectural decisions, not code bugs. I prioritize upfront design decisions that prevent cascading failures before they happen.
- Microservices & Domain-Driven Design (DDD)
- Event-Driven Architectures with distributed workflows
- Distributed Transactions & idempotent operations
- Scalability Patterns: Horizontal scaling, load balancing, sharding strategies
- Resilience Engineering: Circuit breakers, retries, timeouts, graceful degradation
- System Observability: Logging, metrics, tracing, alerting
| Area | Technologies |
|---|---|
| Languages | PHP (Laravel), Node.js (NestJS, Express), Python (FastAPI), Java (Spring Boot) |
| Frameworks | Laravel, Symfony, Express, NestJS, FastAPI, Spring Boot, NextJS, ReactJS, VueJS |
| API Design | REST, GraphQL, SOAP, gRPC, OpenAPI/Swagger |
- Relational: MySQL, PostgreSQL (optimization, indexing, query planning)
- NoSQL: MongoDB, Redis (caching, sessions, real-time data)
- Search: Elasticsearch, vector databases (semantic search, RAG)
- Data Warehousing: Basic OLAP patterns and analytics
- Message Brokers: Kafka, RabbitMQ, MQTT
- Event Streaming: Real-time pipelines, event sourcing patterns
- Message Queue Design: Idempotence, ordering guarantees, dead-letter handling
- Retrieval-Augmented Generation (RAG): Semantic search, context retrieval, vector embeddings
- LLM Workflows: Prompt engineering, streaming responses, context management, fallback strategies
- AI Backend Patterns: Caching, rate limiting, token optimization, multi-model orchestration
- Container Orchestration: Docker, Docker Compose, Kubernetes basics
- Cloud Platforms:
- AWS: ECS, EC2, S3, Lambda, RDS, SQS/SNS
- DigitalOcean: Droplets, managed databases, Kubernetes
- Cloudflare: Edge computing, CDN, DDoS protection, Workers
- CI/CD: GitHub Actions, GitLab CI, automated testing pipelines
- Infrastructure as Code: Docker, Terraform basics
- MCP (Model Context Protocol) systems and AI-native tooling
- AI-Native Backend Architectures: LLM-powered backends, autonomous systems
- Developer Automation: Scalable tooling, internal platforms
- Performance Optimization: Database optimization, caching strategies, bottleneck analysis
Real-Time Distributed System | High-Concurrency Transactions
Context: Integrated global distribution systems (Amadeus, Navitaire, NDC) for real-time flight booking.
Key Achievements:
- Solved high-concurrency booking failures affecting transaction throughput
- Implemented idempotent distributed transactions to handle retry scenarios safely
- Redesigned API layer to reduce timeout issues and improve response times
- Designed for eventual consistency across multiple external systems
Technologies: PHP/Laravel, PostgreSQL, Redis, RabbitMQ, REST APIs
Real-Time Telemetry System | Edge Computing
Context: Built a platform processing real-time data from 100+ industrial devices with millisecond-level latency requirements.
Key Achievements:
- Designed event-driven architecture with low-latency processing pipelines
- Implemented MQTT ingestion layer for device communication
- Built real-time dashboards and alerting systems
- Structured data pipeline to be AI-ready for predictive maintenance
Technologies: Node.js, MQTT, Kafka, MongoDB, InfluxDB, Elasticsearch, React
Intelligent Matching System | LLM-Integrated Workflows
Context: Leading backend development for an AI-driven education platform connecting teachers and students.
Key Achievements:
- Architected intelligent matching algorithm (teacher ↔ student pairing)
- Integrated LLM-based workflows for content generation and adaptive learning
- Designed AI-assisted development lifecycle with automated testing
- Built scalable backend supporting thousands of concurrent users
Technologies: Node.js/NestJS, Python/FastAPI, PostgreSQL, Redis, OpenAI API, Pinecone
- Systems Built: 15+ production systems handling millions of daily transactions
- Scale Managed: Systems processing 1M+ events/day, serving 100K+ concurrent users
- Availability: Architected systems with 99.9%+ uptime SLAs
- Performance: Optimized APIs reducing p95 latency by 60-70% through caching and indexing
- Team Leadership: Mentored 20+ engineers, established coding standards and architectural patterns
- Designing AI-native backend systems that leverage LLMs as core infrastructure
- Building event-driven microservices at enterprise scale (1M+ events/day)
- Developing MCP-powered automation tools for developer productivity
- Improving system observability and reliability engineering practices
- Exploring vector databases and semantic search applications
| Project | Description | Technologies |
|---|---|---|
| 🔹 Microservices Boilerplate | Production-ready microservices architecture | NestJS, PostgreSQL, Kafka, Docker |
| 🔹 Airline Booking System | Distributed system with multi-GDS integration | Laravel, MySQL, RabbitMQ |
| 🔹 RAG Backend Framework | AI-powered knowledge retrieval system | FastAPI, Pinecone, OpenAI |
| 🔹 IoT Streaming Platform | Real-time telemetry processing | Node.js, MQTT, InfluxDB |
- Team Leadership: Managed and mentored engineering teams of 7–10 engineers
- Full-Stack Delivery: Led projects from architectural design → implementation → production scaling
- International Collaboration: Worked with distributed teams across timezones (Japan, USA, Europe, India)
- Cross-Functional: Collaborated with Product, DevOps, QA, and leadership on strategic initiatives
- SaaS Platforms (B2B)
- Travel & Hospitality (GDS Integration)
- Manufacturing & IoT
- EdTech & Education Technology
- Enterprise Software
- Active in distributed systems and cloud-native communities
- Regular participation in system design discussions and architecture reviews
- Exploring emerging technologies: AI backends, edge computing, real-time systems
- Contributor to open-source projects focused on backend tooling
✅ Senior Backend Engineer / Technical Lead roles (Global / Remote)
✅ System Design Consulting and architecture reviews
✅ AI + Backend collaboration on innovative projects
✅ Mentorship opportunities for aspiring engineers
✅ Technical discussions on distributed systems and scalability challenges
| Platform | Link |
|---|---|
| [email protected] | |
| GitHub | @utpal21 |
| Utpal Biswas |
Feel free to reach out for:
- Collaboration on backend/AI projects
- System design discussions
- Technical mentorship
- Speaking opportunities
Good engineers write code.
Great engineers design systems.
The best engineers design systems that don't break in production.
My mission: Build reliable, scalable systems that teams trust and customers depend on.
Last Updated: April 2026 | View Profile Activity