Ankit Pradhan

Senior Software Engineer

Building production-grade distributed systems that handle millions of transactions. Specializing in scalable backends, cloud infrastructure, and event-driven architectures that survive real-world chaos.

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Core Technologies

Node.js NestJS TypeScript React NextJS PostgreSQL MongoDB Redis AWS Kubernetes Kafka Docker Terraform gRPC

Explore detailed experience, projects, and technical depth below

Career Journey

Building scalable systems across industries

Senior Software Engineer

Progressive Labs • Sep 2024 – Present

Tech Stack:
  • Node.js
  • NestJS
  • TypeScript
  • NextJS
  • AWS (Fargate, EKS, S3, SQS, Lambda)
  • Kubernetes
  • KEDA
  • Orkes Conductor
  • PostgreSQL
  • Redis
  • gRPC
  • GitHub Actions
  • Terraform

Key Achievements

  • High-Volume Export Pipeline: Architected and deployed a scalable, event-driven PDF generation system processing 100,000+ documents in under 60 minutes using Kubernetes, KEDA autoscaling, and distributed workers.
  • Distributed Locking Framework: Designed cluster-aware locking mechanisms enabling safe bulk operations across millions of entities while preventing race conditions and ensuring data consistency.
  • Payment Processing Platform: Built a resilient financial transaction system handling 50,000+ daily payments with full audit trails, reconciliation workflows, and real-time monitoring.
  • Multi-Vendor Data Ingestion Engine: Developed a flexible ingestion pipeline normalizing CSV, XML, and fixed-width client formats, reducing customer onboarding time by 60%.
  • Cloud Infrastructure Optimization: Reduced cloud spend by 30% through intelligent autoscaling policies, resource optimization, and containerization best practices.

Software Engineer

Proshore • Sep 2022 – Jul 2024 • 1 year 11 months

Tech Stack:
  • Node.js
  • Spring Boot
  • Java
  • React
  • Kafka
  • gRPC
  • GCP
  • Kubernetes
  • Flux
  • GitHub Actions

Key Achievements

  • Frontend Performance Optimization: Optimized frontend bundle size and implemented code-splitting, reducing initial page load time by 45% and significantly improving Core Web Vitals.
  • Automated CI/CD Pipeline: Built end-to-end CI/CD pipelines using GitHub Actions and GCP, cutting deployment cycles by 70% and enabling reliable daily releases.
  • Real-Time Event Streaming Platform: Developed Spring Boot and Kafka-based microservices for real-time blockchain transaction streaming, supporting high-throughput operations.
  • Blockchain Network Migration: Assisted in a zero-downtime migration from Ethereum to Solana, increasing transaction throughput while significantly reducing operational costs.
  • End-to-End Testing Framework: Implemented Cypress-based E2E testing with 85% regression coverage, improving QA efficiency and overall system stability.

Backend Engineer

Code Himalaya • May 2022 – Aug 2022 • 4 months

Tech Stack:
  • Node.js
  • Express
  • WebSockets
  • OAuth 2.0
  • MongoDB

Key Achievements

  • Developed reusable WebSocket templates for real-time bidirectional communication features
  • Implemented secure OAuth 2.0 authentication flows with token refresh mechanisms
  • Built RESTful APIs with comprehensive error handling and validation

Junior Software Engineer

TechKilla • Nov 2020 – Jun 2021 • 8 months

Tech Stack:
  • JavaScript
  • Node.js
  • HTML/CSS
  • Express

Key Achievements

  • Developed core components for virtual event platforms handling high concurrent users
  • Researched and documented scalable architecture patterns for real-time applications
  • Contributed to building interactive features for live streaming events

Education & Certifications

Academic foundation and continuous learning

Bachelor of Engineering in Computer Engineering

Khwopa College of Engineering • Tribhuvan University

Nov 2017 – Aug 2022

  • Graduated with distinction (80%+ aggregate performance)
  • Key Courses: Distributed Systems, Cloud Computing, Database Management Systems, Computer Networks, Data Structures & Algorithms, Software Engineering, Operating Systems
  • Final Year Project: Spam Detection Chat Application using Machine Learning (Naive Bayes for text classification, CNN for image spam detection with OCR)
  • Active participant in coding clubs, hackathons, and technical workshops
  • Strong foundation in computer science fundamentals and software engineering principles

Professional Certifications & Training

🎓
Apollo GraphQL

Associate & Professional Developer

Advanced GraphQL schema design, federation, and performance optimization

⚙️
Nepal Engineering Council

Licensed Computer Engineer

Professional engineering license for Nepal

💻
Udemy

Complete Web Developer Bootcamp

Full-stack development, modern frameworks, deployment

🔧
Broadway Infosys

MERN Stack Development

MongoDB, Express, React, Node.js intensive training

Continuous Learning

  • Regular participation in tech conferences and webinars
  • Active on technical blogs and open-source contributions
  • Self-learning: System Design, Microservices Patterns, Cloud Native Architecture
  • Keeping up with latest trends in distributed systems and DevOps

Featured Projects

Personal explorations in AI, algorithms, and interactive experiences

🧠 Smart Semantic Bookmarking & Memory Engine

AI Engineering • RAG Pipeline • NestJS

Technologies:
  • NestJS
  • TypeScript
  • PostgreSQL + pgvector
  • Gemini API
  • Cross-Encoder (ONNX)
  • Drizzle ORM

A production-grade RAG pipeline that turns saved bookmarks into queryable semantic memory — built with the same rigor as a production backend service, not a weekend AI demo.

Key Highlights

  • Hybrid Retrieval + Reranking: Vector search (pgvector HNSW) and Postgres full-text search fused via Reciprocal Rank Fusion, then refined by a locally-run cross-encoder for precision reranking — zero added API cost per query
  • Human-in-the-Loop Review: AI-generated summaries and tags sit in a review queue before ever being embedded; every human correction is logged as future fine-tuning signal
  • Measured, Not Assumed: An LLM-as-judge eval harness scores every answer on relevance and faithfulness — 17/17 golden-set cases passing at 0.94 avg relevance, 1.0 avg faithfulness
  • Agentic Tool Use: Gemini native function calling drives a multi-step control loop that searches, synthesizes, and creates follow-up todos autonomously
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📊 Campus Placement Pipeline

Data Engineering • Databricks • Machine Learning

Technologies:
  • Databricks
  • PySpark
  • Delta Lake
  • Python
  • Random Forest (scikit-learn)
  • FastAPI

A production-style Databricks data engineering project simulating a real-world campus placement analytics system end to end — from raw ingestion to ML-served predictions.

Key Highlights

  • Medallion Architecture: Bronze → Silver → Gold Delta Lake pipeline with per-layer schema validation and dead-letter quarantine for bad records
  • Realistic Scale: Simulates 100,000 students across 150 universities, 500 companies, 50,000 applications, and 80,000 interviews via batch and streaming ingestion
  • ML-Powered Predictions: A Random Forest classifier trained on enriched student features predicts placement outcomes
  • Served via API: A FastAPI layer exposes live ML predictions and pipeline statistics through Databricks Connect
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Open Source Contributions

Published packages and fixes shipped to tools other engineers rely on

⚡ pnpm

Contributor

Fixed an auth config bug affecting both the TypeScript CLI and the newer Rust port — required understanding two parallel implementations of the same behavior and reasoning about cross-platform config resolution, not just a single-language fix.

github logo View Pull Request →

📦 @bro-ankit/nestjs-typeorm-transactional-context

Author • Published npm Package

A NestJS library solving transactional context propagation across async boundaries using AsyncLocalStorage — no decorators, works outside the HTTP request lifecycle. 80+ weekly downloads, used in production fintech systems.

npm logo View on NPM →

🔧 nestjs-sqs

Contributor

Fixed a critical lifecycle bug in message handler wrapping — required digging into NestJS's internal dependency injection and module lifecycle to trace, a good example of production debugging beyond application code.

github logo View Pull Request →

Technical Writings

Sharing knowledge about software engineering and system design

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