AI Product Engineer (Fullstack)

NAS EDUCATION PTE. LTD.; Singapore; On-site; SGD 120,000 - 170,000; Full time

Job summary

NAS EDUCATION PTE. LTD. seeks an AI Product Engineer to own real product problems from discovery through deployment and iteration. You will build production AI systems, connect AI to business workflows, and work directly with customers to understand their needs and context.

You will collaborate across frontend, backend, data, and integrations, turning recurring pain into robust product solutions while continuously learning and improving with feedback and observability.

Qualifications

• Strong software engineering fundamentals and ability to ship and operate real production systems.
• Ability to take ambiguous problems and own them end-to-end.
• Comfortable crossing technical boundaries and learning required skills.
• Meaningful depth in at least one technical area and breadth to collaborate.
• Use AI throughout engineering workflow to research, prototype, write, review, test, and learn.

Responsibilities

• Own product features end to end from discovery to iteration.
• Build production AI systems using tools and customer context.
• Connect AI to real business systems with reliable data flows.
• Work directly with customers to understand their workflow and pain points.
• Turn recurring pain into product by improving data ingestion, integrations, or AI outputs.

Skills

Software engineering

Production systems

Cross-boundary learning

Customer collaboration

AI-driven development

Tools

AI tools

Agent infrastructure

Retrieval systems

Job description

The Role

We're looking for an AI Product Engineer who wants to own real product problems end to end.

We don't separate product engineering from customer problems. Engineers stay close to users and face their real business problems rather than optimize technology in isolation. You might start by understanding a workflow, ingesting and structuring the customer's context, shaping the experience, building across the stack, improving an agent or integration, shipping it, and learning from real use.

You do not need to be an expert in everything. We are building a team of T-shaped engineers: broad enough to own a product experience end to end, with meaningful depth in at least one area such as frontend, backend, mobile, data, AI systems, infrastructure, or integrations.

What You'll Do

• Own product features end to end. Go from discovery and solution design through implementation, testing, deployment, operation, and iteration.
• Build production AI systems. Create agents that use tools and customer context to complete real business workflows, learn through feedback loops and long-term memory, and become more useful over time, supported by practical evaluation and observability.
• Connect AI to real business systems. Build reliable integrations and data flows across advertising, social media platforms, CRM, analytics, payments, and other platforms.
• Work directly with customers. Understand their business, workflow, technology stack, and pain points instead of receiving every problem through layers of abstraction.
• Turn recurring pain into product. When onboarding, data ingestion, an integration, or an AI output is consistently slow, low-quality, or unreliable, find the underlying product, architecture, or agent problem and make the system better for the next hundred customers.

Who You Are

You have strong software engineering fundamentals and experience shipping and operating real production systems. More importantly:

• You can take an ambiguous problem, investigate it deeply, create structure, and own it through to a working outcome.
• You are comfortable crossing technical boundaries and learning whatever the problem requires.
• You have meaningful depth in at least one technical area and enough breadth to collaborate across the rest of the product.
• You care whether what you build creates a useful customer outcome, not only whether the implementation works.
• You use AI throughout your engineering workflow to research, prototype, write, review, test, debug, and learn, while exercising judgment about the quality of its output.
• You understand that production agent engineering is more than prompting and are interested in the systems around the model: tools, context, retrieval, evaluation, state, reliability, and user interaction.
• You communicate openly and are comfortable collaborating with customers, product managers, designers, and other engineers.

Bonus Points

You do not need all of these. We are especially interested if you have depth in one or more of the following:

• You have shipped an LLM- or agent-powered product used by real customers.
• You have hands-on experience with agent evaluation, tool use, retrieval, long-running workflows, or agent infrastructure.
• You have built large-scale data ingestion or synchronization systems.
• You have integrated advertising, social media, CRM, analytics, payment, or other business platforms.
• You have worked directly with customers in product engineering, forward-deployed engineering, solutions engineering, consulting, or an agency.
• You understand marketing workflows, marketing technology, or how businesses acquire and engage customers.

Why Join Us

You will have genuine ownership of both the product and the technology behind it. You will work closely with users and leadership, see the impact of what you build, and have the freedom to challenge how things currently work.

You will not be adding a chatbot to the edge of an established product. You will be building products where agents, context, tools, data, integrations, and user experience are all part of the core architecture.

Our culture is different from a typical software company. We grew from content creation, so we combine engineering rigor with storytelling, speed, experimentation, and a desire to make things people care about. The team shares ownership and passion for the company's success. You grow quickly, build close friendships, and find meaning in creating something ambitious together.