We are working with one of the largest Singapore Banks on a journey of transformation. Leveraging technology and creativity to become a future-ready learning organisation.

They are seeking an experienced Senior AI Engineer to join their team and drive the development of scalable, production-grade AI solutions. The ideal individual will combine deep expertise in artificial intelligence and machine learning with strong software engineering fundamentals, particularly in microservices architecture and multi-language development.

Responsibilities: 

AI/ML Development

• Design, develop, and deploy machine learning models and AI solutions that solve complex business problems.
• Build and implement agentic AI systems with autonomous decision-making, reasoning, and task execution capabilities
• Develop multi-agent systems that use tools, planning, and memory.
• Build and optimise large-scale ML pipelines for training, evaluation, and inference.
• Implement state-of-the-art algorithms in areas such as natural language processing, computer vision, recommendation systems, or predictive analytics
• Conduct experiments, perform model evaluation, and iterate on ML solutions to improve performance.
• Stay current with the latest AI/ML research and identify opportunities to apply emerging techniques.

Software Engineering & Architecture

• Design and implement robust microservices architectures for AI/ML applications
• Build scalable, maintainable, and well-documented code across multiple programming languages.
• Develop RESTful APIs and event-driven systems to integrate AI capabilities into broader platforms
• Ensure high availability, fault tolerance, and performance optimisation of AI services.
• Implement CI/CD pipelines for automated testing and deployment of ML models.

Technical Leadership

• Mentor junior engineers and data scientists on best practices in AI engineering and software development
• Lead technical design discussions and contribute to architectural decisions.
• Collaborate with cross-functional teams, including product managers, data scientists, and platform engineers.
• Conduct code reviews and promote engineering excellence across the team
• Drive technical innovation and champion the adoption of new tools and methodologies

Required Qualifications

Technical Skills

• AI/ML Expertise – 5+ years of experience developing and deploying machine learning models in production environments
• Agentic AI – Experience building autonomous AI agents with capabilities including tool use, reasoning, planning, and multi-step task execution
• Programming Languages – Advanced proficiency in at least Python and Java.
• Experience with Deep learning frameworks (TensorFlow, PyTorch), data processing (pandas, NumPy), ML libraries (scikit-learn), etc.
• Experience with Spring Boot, microservices frameworks, and concurrent programming.
• Microservices Architecture – 5+ years of hands-on experience designing and implementing microservices-based systems
• ML Operations – Experience with MLOps practices, model versioning, monitoring, and deployment strategies
• Cloud Platforms – Proficiency with AWS, GCP, or Azure ML services and infrastructure

Additional Technical Requirements

• Strong understanding of distributed systems, message queues (Kafka, etc.), and event-driven architectures
• Experience with containerization (Docker) and orchestration (Kubernetes)
• Knowledge of database systems (SQL and NoSQL) and data engineering concepts
• Familiarity with API design principles and RESTful services
• Experience with version control (Git) and collaborative development workflows

Experience

• Bachelor's or master’s degree in Computer Science, Engineering, Mathematics, or a related field (or equivalent experience).
• Proven track record of delivering complex AI projects from conception to production
• Strong problem-solving abilities and analytical thinking
• Excellent communication skills with the ability to explain complex technical concepts to diverse audiences
• Experience working in agile development environments

Preferred Qualifications

• PhD in Machine Learning, Artificial Intelligence, or related field
• Experience with agentic AI frameworks (LangChain, AutoGen, etc.) and agent orchestration patterns
• Hands-on experience implementing Agents patterns such as ReAct, Plain and Execute, etc.
• Hands-on experience with advanced prompting techniques such as Chain-Of-Thought, etc.
• Experience with transformer architectures and large language models (LLMs)
• Knowledge of vector databases and retrieval-augmented generation (RAG) systems
• Contributions to open-source AI/ML projects
• Publications in top-tier AI/ML conferences or journals
• Experience with real-time inference systems and model optimisation techniques
• Knowledge of federated learning, edge AI, or distributed training
• Familiarity with MLflow, Kubeflow, or similar ML platforms
• Experience with multiple cloud providers and multi-cloud architectures
• Experience with building LoRA/QLoRA, PEFT pipelines for enterprise-specific tuning
• Experience implementing distributed training pipelines (Ray, FSDP, DeepSpeed, PyTorch Distributed, etc.)
• Experience with integrating continuous feedback loops to improve the model incrementally