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Senior Software Engineer

Nithiwut Wilainuch

Backend-focused engineer specializing in Java, Spring Boot, cloud-native systems, and production reliability.

Senior Software Engineer with 6 years of experience designing and developing backend and web applications across banking and startup environments.

Bangkok, Thailand

About

Backend engineering is the core of my work.

Senior Software Engineer with 6 years of experience designing and developing backend and web applications across banking and startup environments. My strongest areas are Java, Spring Boot, RESTful APIs, relational databases, asynchronous processing, cloud-native delivery, and production reliability.

Designs Java and Spring Boot services, RESTful APIs, relational data access, and asynchronous workflows for production systems.

Improves application and database performance, investigates production issues, and strengthens reliability through root-cause analysis.

Delivers cloud-native systems with AWS, Docker, Kubernetes, and CI/CD across banking and startup environments.

Brings additional full-stack experience with React and Next.js, plus current hands-on work with Angular and NestJS.

Core Skills

A backend-first production toolkit.

Hands-on experience across service development, data-intensive workloads, cloud-native architecture, and reliable delivery.

Frontend experience complements my primary focus on backend, architecture, cloud, and platform engineering.

Languages

  • Java 11-21
  • Python
  • TypeScript
  • JavaScript

Backend

  • Spring Boot
  • Spring Data JPA
  • JDBC
  • NestJS
  • Node.js
  • Django
  • RESTful APIs

Architecture

  • Microservices
  • Event-Driven Architecture
  • Asynchronous Processing

Databases & Search

  • PostgreSQL
  • MySQL
  • Redis
  • Elasticsearch

Cloud

  • AWS S3
  • AWS SQS
  • AWS Lambda
  • API Gateway
  • EKS
  • AWS Batch
  • EventBridge

DevOps & Infrastructure

  • Docker
  • Kubernetes
  • Helm
  • GitLab CI/CD
  • Jenkins
  • Terraform

Engineering Practices

  • Code Review
  • Troubleshooting
  • Root-Cause Analysis
  • Performance Optimization

Frontend / Additional

  • Angular
  • React
  • Next.js
  • HTML
  • CSS

Professional Experience

A backend track record across banking, startup, and public-sector work.

Six years building production services, cloud workflows, and data-driven applications with increasing technical ownership.

Apr 2023 - Present

TTB Bank

Senior Software Engineer

Bangkok

Develops backend systems in banking, including the Roddonjai used-car marketplace and multi-channel lead generation platforms.

  • Design and develop Java and Spring Boot services for Roddonjai, supporting seller onboarding, vehicle inspection, listings, campaign configuration, and internal operations.
  • Co-develop a multi-channel lead generation platform with an external vendor using Angular, Node.js, and AWS Lambda, capturing and routing leads into internal banking systems.
  • Build proof-of-concept and core features for a new internally developed lead generation platform using Angular and NestJS.
  • Optimize high-volume data processing by replacing iterative JPA operations with JDBC bulk operations, reducing unnecessary ORM overhead.
  • Design asynchronous export workflows with AWS SQS and an event-driven S3/Lambda pipeline that produces resized WebP vehicle images.
  • Drive backend upgrades from Java 11 to Java 21, including adoption of modern language features such as records.
  • Support Kubernetes production workloads through application and deployment troubleshooting, root-cause analysis, reliability improvements, technical design, code reviews, estimation, and cross-functional delivery planning.
Java 11-21Spring BootJPA / JDBCNestJSAWSPostgreSQLRedisElasticsearchKubernetes

May 2021 - Mar 2023

Purple Ventures Company Limited

Software Engineer

Bangkok

Developed and supported production backend services using Java, Python, and AWS Serverless technologies in a startup environment.

  • Built Lambda-based APIs and background workflows for production services using Java, Python, and AWS Serverless.
  • Replaced manual ZIP deployments with automated CI/CD pipelines, using Docker and Jenkins to make releases more consistent.
  • Developed internal promotion verification services for call-center workflows and reporting services with automated email delivery.
  • Investigated production issues and coordinated with engineering and data teams to restore and improve service behavior.
JavaPythonAWS LambdaAPI GatewayDockerJenkinsCI/CD

Jun 2020 - Apr 2021

Institute of Public Policy and Development

Backend Developer

Bangkok

Built public-policy applications and data workflows, establishing an early full-stack foundation.

  • Developed Django and PostgreSQL backend services and REST APIs.
  • Implemented frontend experiences with React and Next.js, and maintained ETL and data pipelines.
DjangoPostgreSQLREST APIsReactNext.jsETL

Engineering Ownership

Senior contribution beyond implementation.

Technical input, delivery support, and cross-functional collaboration without overstating formal authority.

Technical contribution

Contributes to technical discussions and design decisions, reviews code, and helps teams converge on maintainable implementation approaches.

Planning and delivery

Breaks down work, supports estimation and delivery planning, and coordinates with BA, SA, QA, architects, vendors, operations, and engineers.

Team enablement

Helps onboard team members by sharing system context, architecture, development workflows, and practical project setup knowledge.

Production decisions

Supports troubleshooting and root-cause analysis, then helps turn production findings into concrete reliability improvements.

Engineering Highlights

Case studies from real production work.

Selected backend challenges, the engineering approach behind them, and the value of each design—without invented metrics or duplicated resume bullets.

Banking systems integration

Multi-channel Lead Generation Platform

Problem
Leads arrive from multiple channels and need to reach internal banking systems through dependable, maintainable workflows.
Engineering approach
Co-develop the current platform with a vendor using Angular, Node.js, and AWS Lambda, while exploring a parallel internal implementation with Angular and NestJS.
Engineering value
Creates a clearer path for channel integration and informs migration and rebuild decisions without tying workflows to a single intake source.
NestJSNode.jsAWS LambdaSystem Integration

Backend performance

High-volume Database Processing

Problem
Iterative ORM-based operations add avoidable overhead to data-intensive, high-volume workloads.
Engineering approach
Refactor iterative Spring Data JPA operations into explicit JDBC bulk operations designed around the workload.
Engineering value
Reduces unnecessary ORM work and makes large data-processing paths more efficient and predictable.
Spring Data JPAJDBCRelational Databases

Long-running workflows

Asynchronous Export Processing

Problem
Large report and data exports should not hold open synchronous API requests while processing completes.
Engineering approach
Queue export jobs with AWS SQS and let background workers process them independently from the request-response lifecycle.
Engineering value
Decouples long-running work from APIs and provides a clearer model for export result and status handling.

Conceptual workflow

  1. API
  2. SQS
  3. Background Worker
  4. Export Result / Status
AWS SQSAsync ProcessingBackground Workers

Cloud-native media processing

Event-driven Image Optimization

Problem
Serving original vehicle images increases delivery bandwidth and cost when smaller presentation-ready assets are sufficient.
Engineering approach
React to S3 upload events with AWS Lambda and automatically generate resized WebP variants.
Engineering value
Moves image transformation out of the request path and supports more efficient image delivery through reusable optimized assets.

Conceptual workflow

  1. Image Upload
  2. Amazon S3
  3. S3 Event
  4. AWS Lambda
  5. WebP Variants
Amazon S3AWS LambdaEvent-DrivenWebP

Used-car marketplace

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Roddonjai Marketplace Backend

Problem
A customer-facing marketplace needs coordinated backend workflows across sellers, inspections, vehicle listings, campaigns, and internal operations.
Engineering approach
Develop Spring Boot services and integrations using relational data, Redis, and Elasticsearch, with backend integrations to OCR and image categorization services where required.
Engineering value
Provides a maintainable backend foundation for marketplace operations, search, supporting workflows, and ongoing production support.
Spring BootRedisElasticsearchBackend integration with AI-powered services

Architecture

Production workflows, made concrete.

Two patterns used in real backend work: queue-based processing for long-running exports and event-driven transformation for vehicle images.

Resume-backed systems

System flow

Asynchronous export processing

A queue separates API response handling from report and data-export workloads that may take longer to complete.

  1. 01

    Client / API

    Accept and validate the export request.

  2. 02

    Backend Service

    Create the job and publish work for processing.

  3. 03

    AWS SQS

    Buffer and decouple the long-running task.

  4. 04

    Background Worker

    Generate the requested report or dataset.

  5. 05

    Storage / Status

    Store the result and expose job status.

System flow

Event-driven image processing

S3 events trigger media transformation automatically after vehicle images are uploaded.

  1. 01

    Image Upload

    Receive the original vehicle image.

  2. 02

    Amazon S3

    Persist the source asset in object storage.

  3. 03

    S3 Event

    Emit an event when the image is stored.

  4. 04

    AWS Lambda

    Resize and convert the source image.

  5. 05

    Optimized WebP

    Store presentation-ready image variants.

Education

Computer engineering foundation.

Bachelor of Engineering, Computer Engineering from Chulalongkorn University, Bangkok.

Senior Project

License Plate Recognition Using Deep Learning

  • Built a license plate recognition system using YOLO transfer learning, Python, and Keras.
  • Deployed the application to Google Cloud Run using containerized deployment.

Resume

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View the concise version of my experience, skills, and professional background.