AI Product Analyst

Nicoll Curtin; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Nicoll Curtin is seeking an AI-focused engineer to work at the intersection of AI agents, automation, and real business challenges. You will partner with product managers, data scientists, and stakeholders to shape and deliver impactful AI products across internal and external platforms.

You will own the backend, orchestrate models, ensure reliability, and drive architectural decisions while shipping features that scale to global users.

Qualifications

• At least 3 years of full-time engineering experience with end-to-end product ownership.
• Strong backend foundation in system design, databases, caching, and message queues.
• Experience across APIs, infrastructure, frontend, and product metrics.
• Fluent in LLM product patterns: chat, copilots, RAG, agentic AI-harness.
• Proficient in reading and modifying code across common backend languages.
• Strong cross-functional collaboration with product, data science, business, operations, and end-user teams.
• Open-minded, agile, and proactive mindset with a willingness to learn.
• Strong sense of responsibility and accountability in delivering quality work on time.

Responsibilities

• Build AI products end to end alongside an AI Product Manager, from discovery and prototyping to shipping, measuring, and iterating.
• Own the full backend of an AI product, including model orchestration, retrieval layers, APIs, data flow, storage systems, and middleware.
• Set technical direction for the systems you own, make architecture decisions, and uphold high standards for code quality and review.
• Strengthen the foundations that make AI products reliable, including evaluations, guardrails, fallbacks, human-in-the-loop workflows, and clear error handling when models fail.
• Operate the products you build end to end, taking ownership of monitoring, incident response, and quality investigations.
• Select the right techniques and tools for each problem, including prompting, RAG, fine-tuning, agents, and classical ML.

Skills

Backend systems

Distributed systems

APIs

Frontend integration

LLM patterns

Agentic AI

Code reading

Collaboration

Proactive mindset

Job description

You will work at the intersection of AI agents, automation, and real business challenges. You will partner closely with product managers, data scientists, and business stakeholders to own, shape and deliver impactful AI products. These projects span both internal and external products, including AI-powered operational tools, AI-driven agents and game localization platforms, supporting real-time interactions and global users at scale.

Job Description

• Build AI products end to end alongside an AI Product Manager, from discovery and prototyping to shipping, measuring, and iterating.
• Own the full backend of an AI product, including model orchestration, retrieval layers, APIs, data flow, storage systems, and middleware.
• Set technical direction for the systems you own, make architecture decisions, and uphold high standards for code quality and review.
• Strengthen the foundations that make AI products reliable, including evaluations, guardrails, fallbacks, human-in-the-loop workflows, and clear error handling when models fail.
• Operate the products you build end to end, taking ownership of monitoring, incident response, and quality investigations.
• Select the right techniques and tools for each problem, including prompting, RAG, fine-tuning, agents, and classical ML.

Job Requirements

• At least 3 years of full-time engineering experience, with a track record of 0-to-1 and end-to-end product ownership.
• Strong backend foundation in system design, distributed systems, databases, caching, and message queues.
• Comfortable working across the stack, including APIs, infrastructure, frontend, and product metrics.
• Fluent in LLM product patterns such as chat, copilots, RAG, agentic AI-harness, with sound judgment and proven experience making technical decisions on prompt vs. fine-tune, retrieval vs. long context, and automation vs. human review.
• Proficient in reading and modifying code across common backend languages.
• Strong cross-functional collaboration skills to work effectively with product, data science, business, operations, and end-user teams.
• Open-minded, agile, and proactive mindset with a strong willingness to learn.
• Strong sense of responsibility and accountability in delivering quality work on time.