Senior Forward Deployed Engineer

digital treasures center pte. ltd.; Singapore; On-site; SGD 180,000 - 260,000; Full time

Job summary

digital treasures center pte. ltd. is seeking an experienced AI application engineer to design, build, and deploy AI-enabled workflows for fintech contexts. You will own end-to-end AI solutions across agent workflows, RAG pipelines, and multi-tenant architectures.

You will collaborate with product and operations to deliver reusable microservices, maintain model health, and optimize prompts, while ensuring compliance and cost control in production.

Qualifications

• 8+ years in software development with 4+ years in AI deployment.
• Fintech/payments domain background preferred.
• Proficiency in Python/Java/Go/Rust and microservices.
• Design of service-oriented, multi-tenant architectures.
• Deep knowledge of LLM app tech: prompting, RAG, agents, function calling.

Responsibilities

• Build AI applications on top of LLM APIs for agents, Q&A, reports, and automation.
• Design and implement RAG pipelines, embeddings, vector stores.
• Create AI agents with tool-calling to orchestrate workflows like onboarding and verification.
• Write and optimize prompts; manage multi-turn conversations and memory.
• Package capabilities as reusable microservices.
• Architect modular, multi-tenant AI apps for productization.
• Build monitoring and evaluation systems for model performance and cost.
• Integrate with backend systems for payments, risk, and compliance.
• Ensure stability, scalability, and fault tolerance in production.
• Collaborate with product, operations, and business teams.

Skills

AI application engineering

System architecture design

Cross-functional collaboration

Programming languages (Python, Java,Go

Education

Bachelor's degree or above in CS/AI

Tools

Microservices

Databases & queues

Embedding management

LLM tools

Job description

Job Description & Requirements

Responsibilities

• 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; 8+ years of software development experience, with at least 4 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.