About this role
Financial institutions in the insurance sector need to automate complex workflows and modernize risk assessment through intelligent applications. Capco aims to solve this challenge by hiring an AI Engineer in Singapore to build and scale production-grade machine learning solutions. The selected practitioner will develop multi-agent workflows, train large language models, and ensure that all deployed applications comply with strict banking regulations and data privacy standards.
This position sits within an expanding consultancy environment focused on digital transformation across the APAC region. Candidates who succeed here typically combine deep software engineering fundamentals with hands-on experience in LLMs, RAG architectures, and Python-based frameworks. The role requires someone capable of bridging the gap between technical data science and practical business needs within the financial services domain.
What you will do
- Build multi-agent workflows to optimize business processes within the insurance sector.
- Develop and maintain software pipelines for data processing, model training, and deployment using Python-based frameworks.
- Train, fine-tune, and optimize neural network models and large language models for risk assessment and customer query resolution.
- Collaborate with data scientists, engineers, and business stakeholders to turn technical requirements into production-ready applications.
- Ensure all artificial intelligence models adhere to banking regulations, data privacy standards, and ethical AI practices.
- Monitor deployed solutions in production environments while troubleshooting issues and implementing necessary updates.
- Participate regularly in team code reviews, agile ceremonies, and continuous integration and deployment processes.
What you need
- Bring three to twelve years of professional experience in artificial intelligence and machine learning engineering with a focus on software development.
- Demonstrate strong software engineering capabilities utilizing Python, Java, React Next, and Node.js.
- Possess hands-on experience in training and fine-tuning neural network models while optimizing for performance and scalability.
- Show proven expertise in working with large language models and building agentic solutions using frameworks like LangChain, LangGraph, or ADK.
- Maintain familiarity with major cloud platforms including AWS, Azure, and Google Cloud for model deployment and data management.
- Apply a solid understanding of machine learning concepts such as supervised learning, evaluation metrics, and bias mitigation.
- Utilize version control systems like Git and adhere to agile methodologies within collaborative team settings.
Nice to have
- Experience in financial services domains
- Familiarity with big data tools and SQL or NoSQL databases
- Knowledge of graph databases and knowledge graphs
- Understanding of DevOps practices, containerization, and MLOps workflows
- Publications, open-source contributions, or certifications in AI and machine learning
Skills and tech stack
Questions candidates ask
What is the location for this role?
This position is based in Singapore as part of the local team supporting the APAC region.
What kind of experience is required for applicants?
Candidates need three to twelve years of professional experience in AI and machine learning engineering, focusing on software development and deployment.
What technologies will I be working with?
The tech stack includes Python, Java, React Next, Node.js, LangChain, LangGraph, ADK, and major cloud platforms such as AWS, Azure, and Google Cloud.