AI Engineer

Capco

Capco is a leading global technology and management consultancy that excels in driving digital transformation within the financial services and insurance sectors. With an unwavering commitment to delivering practical solutions we empower our clients to navigate the complexities of todays fast-paced market. Our integrated services span across major financial hubs worldwide ensuring that we are always close to our clients and their needs.

At Capco we possess not only the expertise but also the vision and passion necessary to lead transformative change. As we embark on an exciting growth journey this is the perfect moment to join our team. We are expanding geographically increasing our workforce and poised to disrupt the consulting landscape across APAC with our entrepreneurial spirit and agile methodologies.

About the Role

We are thrilled to introduce an opportunity for a talented AI Engineer to join our Hong Kong team. This role is designed for a technology innovator who thrives on solving complex challenges and is passionate about building AI-driven solutions that transform the Financial Services industry. As an AI Engineer at Capco you will play a pivotal role in shaping the future of banking and insurance by leveraging cutting-edge AI technologies to deliver intelligent scalable and compliant solutions. Your work will enable our clients to unlock new efficiencies enhance customer experience and stay ahead in a rapidly evolving digital landscape. If you are excited about applying advanced AI techniques to real-world business problems and driving measurable impact we want you on our team.

Key Responsibilities

• Build multi-agent workflows to optimize business processes within banking and financial services.
• Develop and maintain software pipelines for data processing model training and deployment using Python-based frameworks.
• Train fine-tune and optimize neural network models including LLMs for specific use cases such as risk assessment and customer query resolution.
• Collaborate with data scientists engineers and business stakeholders to translate requirements into production-ready AI applications.
• Ensure AI models adhere to banking regulations data privacy standards (e.g. GDPR CCPA) and ethical AI practices.
• Conduct experiments evaluate model performance and iterate solutions to improve accuracy and efficiency.
• Monitor deployed solutions in production troubleshooting issues and implement updates as needed.
• Stay updated on emerging AI trends particularly in NLP and LLMs and contribute to knowledge sharing within the team.
• Participate in code reviews agile ceremonies and CI/CD processes.

Experience and Qualifications

• 410 years of professional experience in AI/ML engineering with a focus on software development and deployment.
• Strong software engineering experience with Python and libraries such as TensorFlow PyTorch scikit-learn and Huggingface.
• Demonstrated experience in NLP including projects involving text classification entity recognition or similar.
• Hands-on experience training and fine-tuning neural network models with a track record of optimizing for performance and scalability.
• Proven expertise working with LLMs (e.g. GPT BERT) and building agentic solutions using frameworks like LangChain LangGraph or ADK.
• Familiarity with cloud platforms (AWS Azure or Google Cloud) for model deployment and data management.
• Solid understanding of machine learning concepts including supervised/unsupervised learning evaluation metrics and bias mitigation.
• Experience with version control systems (e.g. Git) and agile methodologies.
• Excellent problem-solving skills and ability to work in a fast-paced collaborative environment.

Preferred Qualifications

• Experience in financial services domains such as fraud detection credit scoring or customer service automation.
• Familiarity with big data tools (e.g. Spark Hadoop) and databases (SQL/NoSQL).
• Knowledge of graph databases and knowledge graphs.
• Understanding DevOps practices containerization (Docker Kubernetes) and MLOps workflows.
• Publications open-source contributions or certifications in AI/ML.
• Strong communication skills for presenting technical concepts to non-technical stakeholders.