- Singapore
Sea Limited Hiring! Full Time Senior AI Engineer in - Ricebowl
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Job Description
Responsibilities
About Team
We are building the next generation of AI Agentic capabilities for one of our core enterprise products, evolving it from a productivity tool into an intelligent assistant that can understand context, take actions, and get work done autonomously on behalf of our users.
As a senior member of the team, you will work as a close technical partner to our Product Manager, shaping the product direction from a technical feasibility standpoint while owning the architecture and delivery of our AI Agent products end to end.
Job Description
- Lead the technical architecture and end-to-end development of AI Agentic products for a core enterprise platform, partnering closely with the Product Manager to shape product direction from a technical feasibility standpoint.
- Architect and build scalable agent frameworks (multi-step reasoning, tool/function calling, memory, orchestration across multiple LLMs and services) that power our product's copilot and automation features.
- Own the full lifecycle of AI features — technical design, model selection/fine-tuning, evaluation, production deployment, and monitoring — ensuring reliability, latency, and cost efficiency at scale.
- Mentor junior AI engineers, set best practices for prompt engineering, RAG pipelines, and agent evaluation, and help build reusable AI infrastructure for the broader team.
- Partner cross-functionally with product, design, backend/infra, and security teams to ensure AI features are robust, safe, and compliant with data governance requirements.
- Stay on top of the latest advances in LLMs and agentic AI, and proactively identify opportunities to apply new techniques to our product roadmap.
Requirements
- Bachelor's degree or above in Computer Science, Artificial Intelligence, or a related field; a Master's degree is a plus.
- Minimum 5 years of software engineering experience, including at least 2 years of hands-on experience building AI/ML or LLM-powered systems in production.
- Deep expertise in LLM application development: prompt engineering, RAG, agent frameworks (e.g. LangChain, LlamaIndex, AutoGen), tool/function calling, and multi-agent orchestration.
- Strong foundation in machine learning/deep learning, with practical experience in model fine-tuning, evaluation, and optimization (latency, cost, accuracy trade-offs).
- Proven track record of shipping AI-powered products end-to-end, from prototype to production, ideally in a B2B/enterprise or SaaS setting.
- Excellent system design skills, able to architect scalable, secure, and maintainable AI infrastructure.
- Fast learner with a strong self-driven mindset and a bias for action; comfortable navigating ambiguity and driving technical decisions independently.
- Strong communication and collaboration skills, able to partner closely with product managers and designers to translate business needs into technical solutions.
- Experience with enterprise SaaS, productivity platforms, or AI copilot products is a strong plus.
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