Who Are We?
dtcpay is a MAS licensed payment service provider that bridges traditional finance and digital assets. We enable businesses to accept and make payments in both fiat and digital currencies, delivering secure, efficient, and seamless payment experiences across borders. As we expand globally, we are shaping the future of digital payments.
We are also recognised as one of Singapore’s Top 10 Startups in the LinkedIn Top Startups 2025 list, a reflection of our momentum and the exciting journey ahead for our team.
We are looking for an AI Application Development Engineer to lead the end-to-end AI engineering and business automation transformation within the cross-border fintech payments and settlement space. You will focus on high-value domains including intelligent risk control, compliance review, merchant operations, and settlement reconciliation — driving AI capabilities from proof-of-concept through to production-grade, scalable, and well-architected systems.
This role requires candidates with both strong software engineering fundamentals and exceptional systems thinking — not only building AI features, but designing service-oriented, modular, multi-tenant, and highly available services, APIs, and data pipelines.
Work Arrangement: Fully On-site
Location: Cecil Street, Singapore
What You'll Do:
- Build intelligent applications on top of large language model APIs, covering Agent workflows, intelligent Q&A, automated report generation, and process automation assistants.
- Design and implement RAG (Retrieval-Augmented Generation) pipelines, including text chunking strategies, Embedding management, vector store integration, and retrieval quality optimization.
- Build AI Agents with tool-calling and function-calling capabilities to orchestrate complex multi-step business workflows such as merchant onboarding review, document verification, and compliance filing.
- Write, evaluate, and optimize prompts to ensure stable, accurate, and business-relevant model outputs; manage multi-turn conversation state and context memory to maintain coherence and reliability.
- Package AI capabilities into reusable, versioned APIs or microservices, following microservices design principles.
- Design the overall architecture of AI applications with service-oriented, modular, and multi-tenant characteristics to support the productization of AI capabilities across different business lines.
- Build automated evaluation, monitoring, and alerting systems to continuously track model performance (accuracy, latency, cost), and iterate on core metrics such as risk control accuracy and human replacement rate.
- Integrate with core backend business systems, complete interface integration and data pipeline setup with payment, risk control, and compliance platforms, ensuring financial-grade security and compliance requirements are met.
- Ensure AI services maintain stability, scalability, and fault tolerance in regulated financial production environments.
- Work closely with product, operations, and business teams to identify and refine AI implementation opportunities.
What We're Looking For:
- Bachelor's degree or above in Computer Science, Artificial Intelligence, or a related field; 5+ years of software development experience, with at least 2 years in AI application engineering and production deployment; fintech / payments industry background preferred.
- Proficiency in Python, Java, Go, or Rust; solid hands-on experience with microservices architecture, caching, databases, and message queues.
- Strong system architecture design skills — able to design AI applications as service-oriented, modular, multi-tenant, and productizable systems, with thorough consideration of stability, observability, and cost control.
- Deep practical knowledge of core LLM application technologies, including Prompt Engineering, RAG architecture design and optimization, Agent framework usage, and Function Calling / Tool Use mechanisms.
- Understanding of business logic in cross-border payments, financial risk control, anti-fraud, and compliance review; hands-on AI experience in financial / payment contexts is a plus.
- Strong problem decomposition skills and cross-functional collaboration abilities; capable of independently driving AI project delivery in a fast-paced environment.
- Able to use English as a working language with strong written and verbal communication skills.
Nice to Have:
- Proven experience delivering AI projects in cross-border payments, e-wallets, acquiring and settlement, or anti-money laundering.
- Proficiency with frameworks such as LangChain, LlamaIndex, or Spring AI, or experience building in-house Agent / RAG platforms.
- Familiarity with vector database selection and Embedding model tuning.
- Experience building observability solutions for large model applications.