Lead of Agentic AI

golden agri international pte ltd; Singapore; On-site; SGD 140,000 - 210,000; Full time

Job summary

Golden Agri International Pte Ltd seeks an experienced AI Engineering Lead to guide engineers and specialists in delivering high-quality AI solutions. You will translate the AI strategy into actionable plans and oversee the end-to-end development of AI agents, copilots, and automated workflows.

The role requires hands-on leadership, 5–9 years in AI/ML roles with 2–3 years in a team lead capacity, and a strong background in enterprise-grade AI platforms and governance.

Qualifications

• Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Information Systems, Software Engineering, or related field; Master’s advantageous.
• 5–9 years in AI/ML engineering or related technology roles; 2–3 years in technical lead or team lead capacity.
• Proven hands-on experience building LLM-based applications, AI agents, or automation workflows.

Responsibilities

• Lead and manage day-to-day activities of AI engineers and specialists; ensure delivery quality and alignment.
• Translate AI strategy into actionable project plans and milestones.
• Provide technical leadership in design, development, and deployment of AI agents and automation workflows.
• Review architectures, code quality, and integration patterns for scalability and maintainability.

Skills

LLM-based apps

Agentic AI

RAG architectures

API integration

AI tooling

Education

Bachelor's degree in CS/AI/DS/IS/Software Eng

Master's degree advantageous

Tools

AI frameworks

Cloud platforms

Governance tools

Job description

MAIN DUTIES AND RESPONSIBILITIES

• Lead, guide, and manage day-to-day activities of Agentic AI Engineers and Specialists, ensuring delivery quality, team alignment, and technical excellence.
• Translate the AI strategy and roadmap defined by the Head of AI-COE (CBS) into actionable project plans, technical designs, and delivery milestones.
• Provide technical leadership and hands-on guidance in the design, development, and deployment of AI agents, copilots, multi-agent systems, and intelligent automation workflows.
• Review and approve AI solution architectures, code quality, prompt engineering standards, and integration patterns to ensure scalability and maintainability.
• Mentor and upskill team members in LLMs, Agentic AI frameworks, RAG architectures, API integration, and modern AI tooling.
• Manage sprint planning, task allocation, progress tracking, and delivery reporting for AI engineering projects within the team.
• Collaborate with business stakeholders, product owners, and technical teams to gather requirements, validate solutions, and drive adoption of AI capabilities.
• Coordinate with the Head of AI on resource planning, risk escalation, AI governance compliance, and strategic prioritisation.
• Drive rapid prototyping, proof-of-concept (POC) initiatives, and innovation experiments, ensuring findings are structured and actionable.
• Monitor AI system performance, reliability, and operational effectiveness; lead continuous improvement efforts and post-deployment optimisations.
• Contribute to the development of reusable AI modules, automation frameworks, documentation standards, and knowledge-sharing practices across the team.
• Support the Head of AI-COE (CBS) in evaluating emerging AI technologies and identifying opportunities for enterprise-wide adoption.

REQUIREMENTS

• Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Information Systems, Software Engineering, or a related field. A Master’s degree is advantageous.
• Preference given to candidates with certifications or specialisation in:
  • Artificial Intelligence & Machine Learning
  • Cloud Platforms & Architecture
  • Enterprise Architecture
  • AI Governance & Responsible AI
  • Agile / Project Management (e.g. Scrum Master, PMP)
• 5-9 years’ experience in AI/ML engineering, software engineering, or related digital technology roles, with at least 2-3 years in a technical lead or team lead capacity.
• Proven hands-on experience building LLM-based applications, AI agents, or automation workflows. Experience leading small-to-medium engineering teams in a fast-pace or agile delivery environment. Background in enterprise or multinational organisations is an advantage.