{"name":"Sujit Kumar Maiti","title":"Backend & AI Infrastructure Engineer","eyebrow":"Backend · Distributed Systems · AI Engineering","tagline":"I build the machinery behind products.","description":"Software engineer focusing on microservices, idempotency patterns, asynchronous queues, and resilient API gateways.","email":"hello@sujitmaiti.cv","site":"https://sujitmaiti.cv","location":"Goa / Remote","social":[{"label":"GitHub","url":"https://github.com/skmaiti2050","icon":"github"},{"label":"LinkedIn","url":"https://linkedin.com/in/skmaiti2050","icon":"linkedin"},{"label":"Résumé [PDF]","url":"/assets/resume.pdf?v=2","icon":"download"}],"projects":[{"name":"Idempotent Task Grid","problem":"In distributed systems, client network timeouts or uncoordinated retries trigger duplicate execution of asynchronous background jobs, corrupting state and doubling compute cost.","system":"Built an ingestion service using FastAPI and Redis. Incoming requests pass an Idempotency-Key header verified atomically via Redis SET NX before dispatching to asyncio.BackgroundTasks. Sliding-window rate limiting prevents request bursts.","result":"Prevents duplicate worker execution on network retries with sub-50ms ingestion latency.","stack":["Python","FastAPI","Redis","Docker Compose","Asyncio"],"url":"https://github.com/skmaiti2050/idempotent-task-grid","repo":"https://github.com/skmaiti2050/idempotent-task-grid","featured":true},{"name":"LLM Observability Gateway","problem":"Capturing granular inference telemetry (token counts, TTFT, model latency, error rates) in streaming LLM requests normally introduces database I/O latency and network jitter into the client stream.","system":"Multi-provider routing gateway in NestJS supporting OpenAI-compatible and Anthropic endpoints over Server-Sent Events (SSE). Streams tokens immediately to the client while offloading inference telemetry payloads to Bull queues backed by Redis.","result":"Maintained low time-to-first-token while capturing structured audit logs and Prometheus metrics asynchronously.","stack":["NestJS","React","Prisma","PostgreSQL","BullMQ","Redis","Prometheus","Grafana"],"url":"https://github.com/skmaiti2050/llm-chatbot","repo":"https://github.com/skmaiti2050/llm-chatbot","featured":true},{"name":"Food Delivery Infrastructure","problem":"Multi-branch restaurant ordering requires determining exact branch delivery zone eligibility from coordinates, while real-time kitchen alerts and Stripe webhook retries must never cause duplicate orders.","system":"NestJS microservices utilizing @turf/boolean-point-in-polygon for delivery boundary validation, partitioned Socket.IO rooms for kitchen dispatch, and cryptographic Stripe webhook signature verification with idempotent event handling.","result":"Reduced p95 response time by 25% and prevented duplicate webhook processing across branch workflows.","stack":["NestJS","TypeScript","PostgreSQL","Redis","Socket.IO","Turf.js","Stripe","Next.js"],"url":"https://cravintechnologies.com","repo":"","featured":true}],"experience":[{"title":"Full Stack Developer","company":"Cravin Technologies LLC FZCO","url":"https://cravintechnologies.com","period":"Dec 2023 to Present","location":"Dubai, UAE","achievements":["Architected backend microservices in <strong>NestJS & PostgreSQL</strong> for food delivery and booking products, cutting p95 response time by 25%.","Collaborated on merchant management interfaces in <strong>Next.js</strong> with live <strong>Socket.IO</strong> feeds and TanStack Query state caching.","Built delivery zone boundary calculations using <strong>Turf.js</strong> geospatial polygon validation and idempotent Stripe webhook processing.","Automated deployment pipelines and container orchestration with <strong>Docker</strong> and <strong>AWS</strong>."],"stack":["NestJS","PostgreSQL","Socket.IO","Turf.js","Stripe","Next.js","Docker","AWS"]},{"title":"Associate Software Engineer","company":"Coditas Solutions LLP","url":"https://coditas.com","period":"Sep 2022 to Nov 2023","location":"Pune, India","achievements":["Engineered enterprise backend microservices in <strong>Node.js & PostgreSQL</strong> for high-throughput client platforms.","Co-architected a serverless background verification system on <strong>AWS Lambda</strong> with asynchronous event queues, <strong>Redis</strong> database caching, and S3 encryption.","Optimized complex PostgreSQL queries and index usage, reducing database CPU load during peak reporting spikes."],"stack":["Node.js","PostgreSQL","Redis","AWS Lambda","TypeScript","Docker"]}],"philosophy":[{"title":"Idempotency over optimism","text":"Networks fail, clients timeout, and users double-click. If a write endpoint is not designed for safe retries, it is broken by default."},{"title":"Decouple persistence from client latency","text":"Synchronous database transactions during live streams or webhook ingest create backpressure. Push telemetry and secondary workflows to asynchronous queues."},{"title":"Quiet, verifiable architectures","text":"Systems become reliable through clear boundaries and observability, not through overly clever abstractions."}],"education":{"degree":"Bachelor of Engineering, Computer Science","institution":"Goa University","location":"Goa, India","year":"Aug 2022"},"skills":{"backend":["TypeScript","Python","Node.js","NestJS","FastAPI","Express.js"],"databases":["PostgreSQL","Redis (SET NX, Pipelines)","MongoDB","BullMQ","Prisma"],"cloud":["AWS (Lambda, SES, S3, EC2)","Docker","Prometheus","Grafana","CloudWatch"],"frontend":["Next.js","React","TanStack Query","TanStack Table","Tailwind CSS"]}}