Senior AI Engineer

About Grab and Our Workplace

Qualifications

• Experience designing and deploying at least one enterprise-grade agentic solution in production, with practical experience in tool integration, orchestration, state and memory management, evaluation, guardrails, observability and failure handling.
• I have hands-on experience with agentic frameworks such as LangGraph, LangSmith, and LangChain. Additionally, I have a understanding of retrieval-augmented generation, LLM orchestration, tool calling, and agent evaluation.
• Transformer Architecture: understanding of transformer architectures, including attention mechanisms, tokenization, positional encoding, training goals, optimization, and inference. You can implement and train a transformer-based model from scratch
• Core ML: Expert proficiency in Python, Spark, and SQL (Presto/Hive) with a command of fundamental ML concepts (Bagging, Boosting, Recommendation Engines)
• AI Productionization: Expertise in deploying scalable AI and ML systems using tools such as MLflow, Kubeflow, TFX, or SageMaker, together with experience in model serving, monitoring, automated evaluation and cloud infrastructure.