Software Engineer (Backend)

Job Title: Software Engineer (Backend), FinTech Platform

Employment Type: Permanent

Location: HK Sheung Wan

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

Essential Requirements:

• 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:

• FinTech, banking, software vendor experience

• 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