Senior AI Engineer

Get to know the team

Grab's Financial Services business is present across 6 countries in South East Asia, in the Payments, Lending, Insurance and Digital Banking domain. We station our engineering teams in India, Singapore, Indonesia, Malaysia and Vietnam. We are excited to provide financial services to all participants of the ecosystem be it our Consumers, Drivers or Merchants. We build our products on fundamental market insights combined with advanced Data Science, Generative AI and engineering to bring the best product market fit across the cross section of our user base. This understanding of our ecosystem combined with world class engineering execution continues to create tremendous value for our customers.

We base the Financial Services Data Science and AI team across Bangalore, Kuala Lumpur, and Singapore. We are looking for an AI Engineer to join and expand our Bangalore team. The AI Engineer will work in a relatively flat team structure with an independent goal of developing critical AI solutions. You will focus on developing enterprise-grade agentic applications, fine-tuning large language models and building transformer-based foundational and promoting models using Grab's rich transactional data. You are passionate about AI and engineering, has and has taken complex AI systems from concept to production. Grab bases this role in its Bangalore office.

The Role:

• Develop an understanding of Grab's Financial Services and Banking data and its nuances across countries. • Deploy enterprise-grade agentic solutions that power the next generation of customer experiences. • Develop AI solutions for use cases such as representation learning, conversational AI and agentic operations. • Fine-tune and adapt LLMs using techniques such as supervised fine-tuning, instruction tuning, LoRa and PEFT. • Build transformer-based models from scratch, including foundational models and promoting models trained on large-scale transactional data. • Manage the complete lifecycle of AI systems from experimentation and evaluation through deployment, optimization, monitoring, and maintenance. • Work with engineering, product, compliance, risk, and operations teams to build reliable and responsible AI solutions. • Stay current with AI and LLM research, frameworks, and new techniques, and translate them into practical applications. • Or collaboratively to solve complex and ambiguous technical problems. • Operate as an individual contributor with 5+ years of relevant experience.

The daily activities:

• Enterprise Agentic AI: Design and deploy production-grade agentic systems using LLM orchestration, tool use, planning, memory, retrieval, and multi-agent workflows. Build for reliability, observability, security, scalability, and human oversight. • LLM Development and Fine-Tuning: Fine-tune and evaluate LLMs using techniques such as supervised fine-tuning, instruction tuning, LoRA, and PEFT. Build high-quality training and evaluation datasets and increase models for accuracy, latency and cost. • Transformer and Foundation Model Development: Design and implement transformer architectures from scratch. Train foundational or domain-specific representation and promoting models using large-scale transactional and behavioural data. • Evaluation and Guardrails: Define offline and online evaluation frameworks for AI agents and models. Develop evaluation datasets, safety guardrails, monitoring systems and feedback loops to improve production performance. • Ownership and Collaboration: Design AI solutions by working backwards from business and customer needs. Lead delivery from problem definition and architecture through production deployment and ongoing operation.