Senior LLM & Autonomous Agent Engineer

amIT Global Solutions Sdn Bhd; Indonesia; On-site; IDR 450,000,000 - 750,000,000; Full time

Job summary

amIT Global Solutions Sdn Bhd in Indonesia seeks a senior ML/LLM engineer to lead end-to-end development of domain-specific large language models. The role emphasizes continuous pre-training, post-training, and the design of autonomous agents to extract and synthesize knowledge for downstream production systems.

You will collaborate across teams to deploy multimodal models, optimize agent workflows, and deliver measurable business impact through content generation, semantic search, and ranking

Qualifications

• Master's degree or higher in CS/NLP/AI or related field.
• Minimum 5 years of full-time industry experience in LLM/ML engineering with large-scale pre-training.

Responsibilities

• Lead continuous pre-training and post-training of large language models for vertical domains.
• Design and build autonomous agents to retrieve, extract, and synthesize domain knowledge.
• Develop RL-based post-training methods to improve QA, reasoning and knowledge modeling.
• Build multimodal LLM applications for content generation and semantic recall.
• Design end-to-end agent workflows integrating query understanding and downstream systems.
• Create generative representation-learning pipelines for downstream ranking and recommendations.
• Collaborate cross-functionally to translate requirements into scalable model training and agent design.

Skills

LLM/ML engineering

Autonomous agents

Multimodal models

Production deployment

Problem solving

Education

Master's degree or above in CS/AI

Tools

LangGraph

Python

PyTorch

TensorFlow

Job description

amIT Global Solutions Sdn Bhd in Indonesia seeks a senior ML/LLM engineer to lead end-to-end development of domain-specific large language models. The role emphasizes continuous pre-training, post-training, and the design of autonomous agents to extract and synthesize knowledge for downstream production systems.

You will collaborate across teams to deploy multimodal models, optimize agent workflows, and deliver measurable business impact through content generation, semantic search, and ranking