Senior Agent Researcher / Engineer

XG TECH PTE. LTD.; Singapore; On-site; SGD 100,000 - 140,000; Full time

Job summary

A leading tech firm in Singapore is seeking a Senior / Staff-level Agent Researcher or Engineer to develop evaluation-driven, system-oriented Agent applications. The role requires designing and optimizing Agent systems, focusing on performance, behavior analysis, and continuous improvement. Ideal candidates will have senior experience with AI systems, solid foundations in machine learning, and a research-oriented mindset. Join to make a significant impact in complex real-world scenarios.

Qualifications

• Proven experience designing and evolving evaluation-driven Agent systems.
• Strong understanding of evaluation, context, and system architecture.
• Familiarity with automated experimentation or A/B testing.

Responsibilities

• Build and evolve evaluation-driven Agent systems.
• Design observable and maintainable Agent systems.
• Develop scalable Agent evaluation infrastructure.
• Optimize Agent architectures and model choices.
• Prototype Agent systems using AI-native development practices.

Skills

Senior / Staff-level experience with Agent, LLM, or complex AI systems

Ability to track advances in Agents, LLM / MLLM, multimodal models

Solid foundations in AI / ML and systems

Experience with Agent evaluation frameworks

Research-oriented mindset

Job description

We are hiring a Senior / Staff-level Agent Researcher or Engineer to work on evaluation-driven, system-oriented Agent and Multi-Agent applications in complex real-world scenarios.

What You Will Do

• Build and evolve evaluation-driven Agent systems, using evaluation as the primary mechanism to guide Agent behavior, iteration, and long-term improvement
• Design Agent systems that are observable, maintainable, and optimizable under real-world constraints
• Develop scalable and automated Agent evaluation infrastructure that can be reused across projects
• Continuously optimize Agent architectures, model choices, context, memory, and tool usage with clear performance–cost trade-offs
• Rapidly prototype Agent systems and demos using AI-native development practices (research × engineering × product validation)

What We Look For

• Senior / Staff-level experience with Agent, LLM, or complex AI systems
• Strong ability to track and internalize advances in Agents, LLM / MLLM, multimodal models, multi-agent systems, and context engineering, and translate them into practical solutions
• Solid foundations in AI / ML and systems, with a deep understanding of models, inference, training, context, evaluation, and system architecture (beyond API-level usage)
• Experience with Agent evaluation frameworks, automated experimentation, or A/B testing
• A research-oriented mindset combined with strong engineering execution

Nice to Have

• Publications, technical blogs, or open-source contributions
• Experience with automotive, chip, or intelligent cockpit systems (a plus, not a requirement)

Keywords

Evaluation-driven Agent · Systems Thinking · Research × Engineering · AI-Native

We are less interested in whether an Agent can simply run, and more focused on how well it performs, why it behaves as it does, and how it can continue to improve over time.