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DBS Bank Ltd

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Associate Senior Associate Agentic AI Engineer Risk Technology Risk Management Group

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Summary

Builds scalable backend services, APIs, and LLM-powered AI agents and multi-agent workflows for DBS Bank's Risk Technology team, including RAG, semantic search, AI evaluation, and guardrails. Day-to-day spans Python/Java microservices, vector databases, CI/CD, and some full-stack work.

You will gather and refine technical and AI requirements with stakeholders. You will build scalable applications, microservices, APIs, LLM-powered features, AI agents, and multi-agent workflows. You will develop backend services, implement retrieval-augmented generation and semantic search, and maintain databases and UI components. You will manage the software lifecycle, CI/CD, deployment automation, monitoring, testing, AI evaluation, and guardrails.

Responsibilities

  • Gather, analyse, and refine technical and AI-related requirements
  • Design, develop, and maintain scalable applications, microservices, and APIs
  • Develop and integrate LLM-powered features
  • Build backend services using Java, Python, Node.js, FastAPI, and Spring Boot
  • Perform prompt engineering, context engineering, and retrieval-augmented generation
  • Build and orchestrate AI agents and multi-agent workflows
  • Integrate LLM APIs and manage vector databases and embeddings for semantic search
  • Develop AI evaluation systems, testing harnesses, and guardrails
  • Design and optimise SQL databases and use ORM tools
  • Contribute to full-stack development and UI/UX
  • Manage development, testing, deployment, and maintenance
  • Implement CI/CD pipelines and support automation, monitoring, and scalability

Requirements

  • Bachelor's degree in computer science, software engineering, or a related field
  • 5+ years of software development experience
  • Proficiency in Python
  • Working knowledge of JavaScript, TypeScript, Java, and Kotlin
  • Experience with FastAPI, Spring Boot, RESTful APIs, and microservices
  • Experience or exposure to LLMs, prompt engineering, or AI application development
  • Understanding of retrieval-augmented generation, embeddings, vector databases, and semantic search
  • Familiarity with LangChain and Agent Harness concepts
  • Knowledge of AI evaluation, guardrails, and hallucination mitigation
  • Understanding of backend architecture, distributed systems, object-oriented programming, and design patterns
  • Proficiency in SQL, relational databases, Hibernate, and JPA
  • Experience with CI/CD, Git, DevOps practices, and deployment automation
  • Communication skills for explaining complex engineering and AI concepts

Skills

See also

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