Senior AI Engineer

OCBC; Singapore; Vor Ort; SGD 120.000 - 180.000; Vollzeit

Zusammenfassung

OCBC Singapore seeks a Senior AI Engineer to drive scalable, production-grade AI solutions. You will combine deep AI/ML expertise with strong software engineering, focusing on microservices and multi-language development.

You will design and deploy ML models, build agentic AI systems with autonomous decision-making, and develop multi-agent workflows. The role also covers robust APIs, CI/CD, and cross-functional collaboration.

Qualifikationen

• 5+ years of experience developing and deploying ML models in production.
• Experience building autonomous AI agents with tool use, reasoning, planning, and execution.
• Proficiency in Python and Java.
• Experience with TensorFlow or PyTorch, pandas/NumPy, and scikit-learn.
• Familiarity with Spring Boot, microservices, and concurrent programming.
• Solid ML Operations, model versioning, monitoring, and deployment practices.
• Experience with cloud ML services (AWS/GCP/Azure).
• Understanding of distributed systems and event-driven architectures.
• Experience with containerization (Docker) and orchestration (Kubernetes).
• Knowledge of SQL/NoSQL databases and RESTful service design.

Aufgaben

• Design, develop, and deploy ML models and AI solutions in production.
• Build agentic AI systems with autonomous decision-making and memory.
• Develop multi-agent systems using tools, planning, and coordination.
• Create large-scale ML pipelines for training, evaluation, and inference.
• Implement state-of-the-art NLP, vision, or analytics techniques.
• Experiment, evaluate, and iterate ML solutions to improve performance.
• Stay current with AI/ML research and apply new techniques.
• Design robust microservices architectures for AI/ML applications.
• Develop RESTful APIs and event-driven integrations into platforms.
• Lead design discussions, conduct code reviews, and promote engineering excellence.

Kenntnisse

AI/ML Expertise

Agentic AI

Programming Languages

Deep learning frameworks

Spring Boot & microservices

ML Ops

Cloud Platforms (AWS/GCP/Azure)

Distributed systems

Docker/Kubernetes

REST APIs

Ausbildung

Bachelor’s degree in Computer Science or related field

Master’s degree (advantage)

Tools

Docker

Kubernetes

Git

Kafka

Jobbeschreibung

WHO WE ARE:

As Singapore's longest established bank, we have been dedicated to enabling individuals and businesses to achieve their aspirations since 1932. How? By taking the time to truly understand people. From there, we provide support, services, solutions, and career paths that meet their individual needs and desires.

Today, we're on a journey of transformation. Leveraging technology and creativity to become a future-ready learning organisation. But for all that change, our strategic ambition is consistently clear and bold, which is to be Asia's leading financial services partner for a sustainable future.

We invite you to build the bank of the future. Innovate the way we deliver financial services. Work in friendly, supportive teams. Build lasting value in your community. Help people grow their assets, business, and investments. Take your learning as far as you can. Or simply enjoy a vibrant, future-ready career.

Your Opportunity Starts Here.

About the Role:

We are seeking an experienced Senior AI Engineer to join our team and drive the development of scalable, production-grade AI solutions. The ideal candidate 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

What we offer:

Competitive base salary. A suite of holistic, flexible benefits to suit every lifestyle. Community initiatives. Industry-leading learning and professional development opportunities. Your wellbeing, growth and aspirations are every bit as cared for as the needs of our customers.