M.S. Computer Science @ Stony Brook University · Systems & Backend Engineer · Distributed Systems

Software engineer with 2+ years of industry experience building high-availability backend systems at scale. Currently architecting high-throughput data pipelines and web infrastructure as a Graduate Research Assistant at Stony Brook. Deeply passionate about distributed systems architecture, event-driven pipelines, and fault-tolerant infrastructure.

📍 Stony Brook, NY  |  📬 rohan.kuckian@gmail.com  |  🔗 LinkedIn

Languages Go (Golang) Java Python SQL PL/SQL TypeScript JavaScript C/C++

Distributed Systems & Messaging Apache Kafka gRPC Multi-Paxos Two-Phase Commit (2PC) Event-Driven Architecture Distributed Locking Write-Ahead Logging (WAL)

Databases & Caching PostgreSQL Redis Oracle 19c MySQL MongoDB BoltDB DynamoDB

Cloud & DevOps AWS (EKS, EC2, S3, Lambda, SQS) Docker Kubernetes Terraform Nginx CI/CD (GitHub Actions, GitLab) Git

Frameworks & Libraries FastAPI Next.js React Tailwind CSS Pandas NumPy PyTorch LangChain

Jan 2025 – May 2026 · Python · Next.js · Tailwind CSS · Docker · Nginx · AWS (EC2) · Pandas

• Architected high-throughput data pipelines in Python utilizing vectorized Pandas operations to process a 100M+ record dataset, boosting ingestion and processing throughput by 50%.
• Engineered an automated, 8-thread distributed scraper using the BlueSky API for daily data archival; containerized and deployed the stack on AWS EC2 using Docker and Nginx reverse proxying.
• Orchestrated the containerization and migration of 11 legacy multi-language applications into a centralized infrastructure, cutting server overhead and modernizing state management.
• Developed a dynamic, fully responsive full-stack web application utilizing Next.js and Tailwind CSS for data visualization, optimizing real-time state synchronization across modular UI components.

Jun 2022 – Jun 2024 · Java · PL/SQL · Oracle 19c · REST APIs · Microservices · Git · Agile

• Developed high-availability backend services for Flexcube core banking systems deployed globally, directly supporting transaction engines processing 20M+ daily transactions.
• Optimized high-volume processing pipelines by engineering custom PL/SQL packages, advanced database indexes, and query joins to handle 1M+ daily records, reducing manual operational workload by 40%.
• Architected and deployed RESTful microservices to integrate 3 distinct core banking models; optimized payload schemas to reduce network data overhead, achieving a 4x acceleration in API delivery frequency.
• Diagnosed and mitigated 10–20 high-priority production and UAT bugs daily under strict SLA metrics, ensuring system stability and zero-downtime customer handovers.
• Leveraged non-linear data structures (advanced tree variations and graph-based routing models) to resolve complex, multi-level branching business logic for mission-critical financial calculations.

Go · Apache Kafka · Redis · PostgreSQL · AWS EKS · FastAPI · LLMs / RAG

• Designing a production-grade distributed streaming platform to ingest 8,000+ events/sec via a Go REST API (Gin), routing live transactional streams through high-throughput Apache Kafka broker clusters.
• Implementing ultra-low latency fraud detection (<5ms) utilizing Redis sliding window counters to track rate-based transaction velocity and maintain a target p99 API latency under 40ms.
• Enforcing system correctness guarantees by integrating unique idempotency keys to prevent database duplication and configuring Kafka consumer groups with a Dead-Letter Queue (DLQ) for automated failure recovery.
• Configuring cloud infrastructure deployment plans targeting AWS EKS with Horizontal Pod Autoscaling, automated GitHub Actions CI/CD pipelines, and full-stack observability via Datadog.
• Integrating an asynchronous Python FastAPI microservice to execute LLM-powered fraud explanations via a Retrieval-Augmented Generation (RAG) pipeline utilizing LangChain and ChromaDB.

Go · Multi-Paxos · Two-Phase Commit (2PC) · BoltDB · gRPC · Protobuf

• Built a sharded, fault-tolerant distributed key-value store in Go supporting atomic read-only, intra-shard, and cross-shard transactions across multi-node clusters.
• Implemented Multi-Paxos for intra-shard consensus and Two-Phase Commit (2PC) for cross-shard atomicity, deploying Write-Ahead Logging (WAL) and distributed locking to preserve absolute ACID compliance.
• Developed an index-based dynamic resharding framework and a custom benchmarking system, achieving a peak performance throughput of 1,038 transactions/sec under intensive workload skew.

React Native · Django · MongoDB · Python · AES Encryption

• Architected cross-platform mobile and desktop infrastructure using Django and MongoDB to handle real-time synchronization pipelines between transit clients and airport staff.
• Optimized backend data transport layers, accelerating image fetch latencies by 20x and sustaining a secure desktop interface response time of <100ms.
• Secured payload transit pipelines by implementing AES encryption standards, mitigating data leakage risks, and ensuring 90%+ user identity data protection across storage nodes.

M.S. Computer Science — Stony Brook University (GPA: 3.77 / 4.0) · 2024–2026

Distributed Systems · Analysis of Algorithms · Data Science Fundamentals · HCI · NLP

B.E. Information Technology — University of Mumbai · 2018–2022

Databases · Web Development · Software Engineering · Artificial Intelligence