Software Engineer (Backend)

Easy View Technology International Limited; Hong Kong; On-site; HKD 600,000 - 900,000; Full time

Job summary

Easy View Technology International Limited is seeking a Backend Software Engineer to build the core services behind a FinTech platform. You will work with AI-assisted development to accelerate delivery while upholding high standards of correctness, security, and compliance.

You will design and implement secure, scalable microservices and REST APIs, leveraging modern AI tools and cloud infrastructure. Strong communication skills are essential to collaborate with stakeholders in a regulated

Qualifications

• Bachelor's degree in Computer Science or related field, or equivalent practical experience.
• 3+ years of professional software development experience.
• Strong Java skills (Java 17+) and Spring Boot.
• Hands-on experience with microservices, REST APIs and messaging systems (e.g., Kafka).
• Experience with AWS cloud platforms, containers (Docker) and CI/CD.
• Daily, practical use of AI coding assistants, and the judgment to know when not to trust them.
• Solid grasp of secure coding practices and data protection basics.
• Strong problem-solving and time management skills.
• Excellent written and verbal communication.
• Proficient in English, Mandarin or Cantonese.

Responsibilities

• Own features across the full software development lifecycle, from design to deployment to monitoring
• Turn business ideas into working, production-ready software, often going from prototype to MVP quickly with AI-assisted development
• Design and maintain microservices, APIs and event-driven systems that are secure, scalable and observable
• Use AI coding tools (e.g., Claude Code, GitHub Copilot, Cursor) for code generation, refactoring, test writing, documentation and debugging
• Critically review all AI-generated code for correctness, security, performance and compliance. You own every line you ship.
• Help define team practices for responsible AI use, such as prompt and context guidelines, review standards and approved tools
• Integrate large language model (LLM) capabilities into backend services, such as retrieval-augmented generation (RAG), document processing, customer support automation and internal productivity tools
• Build supporting infrastructure: model API integration, vector search, guardrails, evaluation pipelines and cost/latency monitoring
• Work with risk and compliance teams to make sure AI features meet regulatory, data privacy and explainability requirements
• Write thorough automated tests (unit, integration, contract), using AI to speed this up without lowering standards
• Support production systems, including incident response, root-cause analysis and continuous improvement
• Build observability into services from the start (logging, metrics, tracing)
• Talk directly with users and stakeholders to gather and clarify requirements
• Work independently in a fast-paced environment with minimal guidance
• Explore new technologies through proofs of concept, including emerging AI tools, frameworks and agent-based workflows, and share what you learn with the team

Skills

Java

Spring Boot

Microservices

REST APIs

Kafka

AWS

Docker

CI/CD

AI tooling

Secure coding

English Mandarin Cantonese

Education

Bachelor's degree in Computer Science

Tools

Kafka

AWS

Docker

CI/CD tooling

Spring Cloud

Job description

Job Title: Software Engineer (Backend), FinTech Platform

Employment Type: Permanent

About Us / Team Introduction

We're looking for a backend engineer to build and run the core services behind our FinTech platform. AI tools are a normal part of how our team works. You'll use AI coding assistants every day to move faster, and you'll help build AI-powered features into our products. Engineering judgment, security and accountability still matter most, because we work in a regulated industry where correctness isn't optional.

What We Value

• Fast learner who adapts: The tools change every few months, and you enjoy keeping up.
• Ownership: AI speeds up the work, but you're still responsible for the result.
• Curiosity with discipline: You're excited by new technology and careful about production risk.
• Clear communicator: You can explain technical tradeoffs to engineers and business stakeholders alike.

Key Responsibilities

Build and Ship

• Own features across the full software development lifecycle, from design to deployment to monitoring
• Turn business ideas into working, production-ready software, often going from prototype to MVP quickly with AI-assisted development
• Design and maintain microservices, APIs and event-driven systems that are secure, scalable and observable

Work Effectively with AI

• Use AI coding tools (e.g., Claude Code, GitHub Copilot, Cursor) for code generation, refactoring, test writing, documentation and debugging
• Critically review all AI-generated code for correctness, security, performance and compliance. You own every line you ship.
• Help define team practices for responsible AI use, such as prompt and context guidelines, review standards and approved tools

Build AI-Powered Features

• Integrate large language model (LLM) capabilities into backend services, such as retrieval-augmented generation (RAG), document processing, customer support automation and internal productivity tools
• Build supporting infrastructure: model API integration, vector search, guardrails, evaluation pipelines and cost/latency monitoring
• Work with risk and compliance teams to make sure AI features meet regulatory, data privacy and explainability requirements

Quality and Reliability

• Write thorough automated tests (unit, integration, contract), using AI to speed this up without lowering standards
• Support production systems, including incident response, root-cause analysis and continuous improvement
• Build observability into services from the start (logging, metrics, tracing)

Collaboration and Exploration

• Talk directly with users and stakeholders to gather and clarify requirements
• Work independently in a fast-paced environment with minimal guidance
• Explore new technologies through proofs of concept, including emerging AI tools, frameworks and agent-based workflows, and share what you learn with the team

Qualifications

• Bachelor's degree in Computer Science or a related field, or equivalent practical experience
• 3+ years of professional software development experience
• Strong Java skills (Java 17+, ideally 21/25) and Spring Boot
• Hands-on experience with microservices, REST APIs and messaging systems (e.g., Kafka)
• Experience with AWS cloud platforms, containers (e.g., Docker) and CI/CD
• Daily, practical use of AI coding assistants, and the judgment to know when not to trust them
• Solid grasp of secure coding practices and data protection basics
• Strong problem-solving and time management skills
• Excellent written and verbal communication
• Proficient in English, Mandarin or Cantonese

Preferred Qualifications:

• Experience building LLM-powered applications (e.g., Spring AI, LangGraph, or the OpenAI/Anthropic APIs)
• Familiarity with RAG, vector databases, embeddings, Model Context Protocol (MCP) or AI agent frameworks
• Understanding of AI evaluation, guardrails and responsible AI principles
• Knowledge of financial regulations and AI governance (e.g., HKMA/SFC guidelines on GenAI, or similar)
• Experience with a second language such as Python, Kotlin or Go