I build scalable systems that power products.

Backend-heavy full stack engineer focused on realtime architectures and distributed systems. Currently engineering analytics infrastructure at Brandlock, processing 1M+ records/day across 200+ merchant clients.

Node.jsPostgreSQLRedisRabbitMQReactAWS
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Numbers from production systems

Real metrics from systems I've designed, built, and maintained at scale.

0%
Onboarding Reduction
15 days → 20 minutes
0M+
Records / Day
Processed through anomaly detection
0+
Monitored Clients
Real-time anomaly surveillance
0%
System Uptime
Across distributed microservices
0x
Services Orchestrated
Event-driven microservice mesh

How I think about systems

Principles and patterns that guide my architectural decisions.

Event-Driven Architecture

Building systems where services communicate through events, not direct calls. RabbitMQ consumers, dead-letter queues, and eventual consistency patterns.

RabbitMQPub/SubAsync
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Caching Philosophy

Multi-layer caching with intelligent invalidation. Not just Redis GET/SET — understanding cache stampedes, write-through vs write-behind, and TTL strategies.

RedisCDNInvalidation
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PostgreSQL Internals

Beyond basic queries — understanding MVCC, query planner behavior, index strategies, and connection pooling for high-throughput writes.

MVCCIndexingPartitioning
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Scaling Challenges

Horizontal vs vertical, stateless services, database connection limits, queue backpressure, and knowing when NOT to scale.

HorizontalLoad BalancingStateless
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Feature Flags

Runtime feature control without deployments. Progressive rollouts, A/B testing infrastructure, and kill switches for safe experimentation.

RolloutsA/B TestingKill Switch
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Distributed Systems

CAP theorem tradeoffs, consensus patterns, idempotency, and the reality of network partitions in production systems.

CAPIdempotencyConsensus
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Realtime Dashboards

Server-sent events, WebSocket connections, efficient DOM updates, and the architecture behind live-updating analytics views.

WebSocketSSELive Data
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Why Architecture Matters

Architecture isn't about diagrams — it's about encoding decisions that compound. Good architecture makes the next 100 features cheaper to build.

ModularityBoundariesDecisions
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Engineering explorations

Production systems and experimental architectures I've built, with the engineering tradeoffs behind each.

Anomaly Detection Engine

Production

Real-time alarm system processing 1M+ records daily, detecting conversion spikes and revenue drops across 200+ merchant clients.

ArchitectureEvent-driven pipeline: PostgreSQL → RabbitMQ → Worker Pool → Alert Router → Notification Service
Node.jsPostgreSQLRabbitMQRedis
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Realtime Analytics Dashboard

Production

Event-driven, API-powered dashboard with live inter-component communication and real-time conversion metrics for e-commerce clients.

ArchitectureReact + Redux → WebSocket Gateway → Express API → PostgreSQL + Redis Cache Layer
ReactReduxWebSocketExpress
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Client Onboarding Automation

Production

Reduced merchant onboarding from 15 days to 20 minutes through automated workflows, cron jobs, and self-service configuration.

ArchitectureCron Scheduler → Validation Pipeline → Config Generator → S3 Asset Upload → GTM Auto-Integration
Node.jsAWS LambdaS3Cron
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Distributed Caching Layer

Production

Multi-tier Redis caching with cascading invalidation, handling 50K+ cache operations per minute across merchant data.

ArchitectureApplication Layer → Local Cache (LRU) → Redis Cluster → PostgreSQL (source of truth)
RedisLRUConsistent Hashing
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NFT Minting Platform (Solana)

Shipped

Web3 gaming platform with NFT/SFT minting using Metaplex, handling 100+ concurrent players with on-chain reward distribution.

ArchitectureReact Frontend → GraphQL API → Loopback 4 → Solana RPC → Metaplex Smart Contracts
SolanaMetaplexGraphQLLoopback 4
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Feature Flag Infrastructure

Experiment

Runtime feature control system enabling progressive rollouts, A/B testing, and instant kill switches without redeployment.

ArchitectureSDK Client → Flag Evaluation Engine → Rule Matcher → Segment Resolver → Redis Cache
RedisNode.jsSDK Design
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HLS Stream Collector

Experiment

Browser extension intercepting video stream URLs from web traffic, with HLS playback preview and regex-based filtering.

ArchitectureChrome Extension (Manifest V3) → WebRequest Interceptor → Stream Parser → HLS.js Player
Chrome APIsHLS.jsManifestV3
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Session Replay Engine

Experiment

rrweb-based session recording platform capturing DOM mutations, user interactions, and network events for debugging.

Architecturerrweb SDK → Event Compressor → S3 Storage → Replay Player → Timeline UI
rrwebDOM APIsS3Compression
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Deep dives & explorations

Topics I study, experiment with, and apply in production. Each entry represents hours of research and practical application.

Data Structures

B+ Tree Indexing

How PostgreSQL uses B+ Trees for efficient range queries and ordered traversal. Understanding node splitting, fill factors, and partial indexes.

// research/b+_tree_indexing.md
Runtime Internals

Node.js Event Loop

The single-threaded model, libuv thread pool, microtask queue priorities, and why understanding the event loop is critical for high-throughput servers.

// research/node.js_event_loop.md
Distributed Systems

Distributed Consensus

Raft, Paxos, and the practical reality of achieving consensus in distributed systems. Leader election, log replication, and split-brain scenarios.

// research/distributed_consensus.md
Databases

Redis Internals

Single-threaded event loop, data structures (skip lists, hash tables), persistence modes (RDB vs AOF), and replication strategies.

// research/redis_internals.md
Performance

Query Optimization

Reading EXPLAIN ANALYZE output, understanding sequential vs index scans, join strategies, and when the planner makes suboptimal choices.

// research/query_optimization.md
Architecture

Realtime Processing

Stream processing vs batch processing, backpressure handling, windowing strategies, and building systems that react in milliseconds.

// research/realtime_processing.md
Performance

System Bottlenecks

Identifying and resolving bottlenecks: database connection pooling, N+1 queries, lock contention, and memory pressure patterns.

// research/system_bottlenecks.md
Architecture

Feature Flag Patterns

Trunk-based development with flags, percentage rollouts, user segment targeting, and the operational cost of long-lived flags.

// research/feature_flag_patterns.md

Where I've engineered impact

Each role was a mission with technical challenges and measurable outcomes.

Brandlock

Software Engineer

Apr 2023 — Present

Mumbai

MISSION: E-commerce Conversion Optimization SaaS

Engineering the backend infrastructure for a conversion optimization platform serving 200+ e-commerce merchants.

98%
Reduced client onboarding time from 15 days to 20 minutes
1M+
Daily records processed through anomaly detection engine
200+
Clients monitored with real-time alerting system
0
Manual monitoring overhead after automation

Key Contributions

  • Automated onboarding workflows using Node.js and cron jobs
  • Built data anomaly alarm system with auto-alert assignment
  • Developed microservices with Express.js, PostgreSQL, Redis, RabbitMQ
  • Built event-driven analytics dashboard with React.js and Redux
Node.jsReactPostgreSQLRedisRabbitMQAWSGTM/GA4

Soulofox Studio

Full Stack Developer

Mar 2022 — Apr 2023

Mumbai

MISSION: Web3 Gaming Platform — NFTs on Solana

Building a real-time Web3 gaming platform with NFT/SFT mechanics on the Solana blockchain.

100+
Concurrent users on real-time gaming platform
0
Downtime during peak gaming sessions
3x
API response time improvement through query optimization

Key Contributions

  • Built real-time Web3 gaming platform with Node.js microservices (Loopback 4)
  • Integrated Solana smart contracts for NFT-based rewards using Metaplex
  • Created RESTful and GraphQL APIs with optimized query performance
  • Improved CI/CD pipelines using Docker and AWS
Node.jsLoopback 4SolanaMetaplexGraphQLDockerAWS