AI Systems Lead

2 weeks ago

Singapore beBeeAgentic Full time $180,000 - $250,000
Senior AI Engineer

We are seeking an experienced and skilled Senior AI Engineer to lead our agentic AI initiatives. This is a unique opportunity to be a foundational member of our technology team, with a primary focus on implementing agentic AI solutions.

Responsibilities:

  • Lead Agentic AI Implementation: Drive the end-to-end development and deployment of agentic AI solutions, including defining agent architectures, designing interaction protocols, and orchestrating multi-agent systems.
  • Research & Innovation: Stay abreast of the latest advancements in agentic AI, large language models (LLMs), reinforcement learning, and other relevant AI domains. Evaluate and propose new technologies and methodologies to enhance our AI capabilities.
  • Solution Design & Architecture: Collaborate with business stakeholders, product managers, and other engineering teams to identify opportunities for AI-driven automation and intelligence. Design scalable, robust, and secure AI architectures that integrate seamlessly with existing systems.
  • Model Development & Training: Develop, train, and fine-tune AI models (including LLMs) to power agentic behaviours, ensuring high performance, accuracy, and ethical considerations.
  • Data Strategy: Work closely with data engineers to define data requirements, ensure data quality, and build robust data pipelines necessary for training and operating AI agents.
  • Deployment & MLOps: Implement best practices for MLOps, including continuous integration/continuous deployment (CI/CD) for AI models, model monitoring, versioning, and lifecycle management of agentic systems.
  • Performance Optimization & Tuning: Monitor the performance of deployed AI agents, identify areas for improvement, and implement optimizations to enhance efficiency and effectiveness.
  • Security & Compliance: Ensure all AI solutions adhere to the highest standards of data privacy, security, regulatory compliance (MAS regulations, etc.), and responsible AI principles.

A successful candidate will possess a strong background in AI/ML engineering, with a proven track record of implementing complex AI solutions. Experience with agentic AI, multi-agent systems, or autonomous intelligent agents is highly desirable. Additionally, proficiency in programming languages such as Python (essential), Java, or C++, as well as extensive experience with AI/ML frameworks and libraries, is required.

Requirements:

  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Robotics, or a related quantitative field.
  • 5+ years of hands-on experience in AI/ML engineering, with a strong portfolio demonstrating successful implementation of complex AI solutions.
  • Deep understanding of Large Language Models (LLMs), their architectures, fine-tuning techniques, and practical applications.
  • Experience with cloud platforms (AWS, Azure, GCP) and their AI/ML services.
  • Familiarity with MLOps tools and practices (e.g., Docker, Kubernetes, MLflow, Kubeflow).
  • Strong understanding of data structures, algorithms, and software design principles.
  • Excellent problem-solving skills, with a methodical and analytical approach.
  • Ability to communicate complex technical concepts effectively to both technical and non-technical audiences.
  • Prior experience in the financial services industry, particularly wholesale banking or digital banking, is a significant plus.

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