AI Engineering Lead (GenAI & Supply Chain Platforms)

BEATHCHAPMAN (PTE. LTD.); Singapore; On-site; SGD 180,000 - 240,000; Full time

Job summary

BEATHCHAPMAN (PTE. LTD.) in Singapore is seeking an AI Engineering Lead to drive GenAI and Supply Chain platform capabilities from concept to production. You will own the architecture, lead LLM integration, and build an internal AI engineering function.

You will report to the CEO and oversee AI engineering, platform, DevOps and infrastructure, modernising legacy systems and delivering AI-enabled products for enterprise customers across APAC.

Qualifications

• Proven production-grade GenAI or LLM system experience.
• Experience in leading multidisciplinary engineering teams.
• Strong understanding of AI safety, privacy, and governance considerations.

Responsibilities

• Own the Generative AI capability from PoC to production.
• Design and deliver LLM-based solutions including RAG and agentic workflows.
• Set technical direction for AI across software estate and modernization.
• Guide integration of legacy systems with cloud-native AI components.
• Lead DevOps and infrastructure teams while building internal AI capability.
• Establish standards for API design, model evaluation, security and observability.

Skills

AI engineering

LLM production

DevOps leadership

Cloud platforms

API design

Education

Bachelors in CS/Engineering

Tools

Azure OpenAI

Google Vertex AI

AWS Bedrock

Job description

Client introduction

Our client is an established Singapore-headquartered supply chain software company with a strong footprint across Asia Pacific. Its software supports complex warehouse, transport, order and broader logistics operations for enterprise customers across the region.

As part of a wider technology transformation, the business is moving its Generative AI capability beyond experimentation and into production. They are hiring a AI Engineering Lead (GenAI & Supply Chain Platforms) to take an existing LLM platform from proof of concept into a production-grade capability, modernise parts of the existing application estate and build out an internal AI engineering function.

The role reports directly to the CEO and carries responsibility across AI engineering, platform, DevOps and infrastructure.

Job responsibilities

• Take technical ownership of the company's Generative AI capability and drive it from proof of concept into a stable, scalable production environment.
• Lead the design and delivery of LLM-based solutions across areas such as RAG, agentic workflows, enterprise integration and AI-enabled applications.
• Set the technical direction for how AI is introduced across the wider software estate, spanning both modernisation of existing applications and new development.
• Guide the integration of legacy Java-based systems with newer cloud-native and AI-enabled components as the technology estate evolves.
• Lead the existing DevOps and infrastructure/server operations teams while progressively building the internal AI engineering capability and developing existing technical staff.
• Establish practical engineering standards across API and integration design, model evaluation, security and privacy, observability and MLOps.
• Evaluate cloud AI platforms, frameworks and supporting technologies, working with selected technology partners where external expertise is required.
• Work closely with product and business stakeholders to identify where AI can improve existing products or enable new capabilities.

Job requirements

• Strong background in software, platform or AI engineering, with the technical depth to operate credibly alongside engineers rather than oversee from a distance.
• Supply chain, logistics, manufacturing or enterprise SaaS experience would be advantageous but is not essential.
• Has taken a Generative AI or LLM-based system into a genuine production environment, with enough technical depth to explain the architecture, engineering decisions and production challenges in detail. Pilots and proofs of concept alone would not be sufficient.
• Practical understanding of modern LLM patterns including retrieval-augmented generation, agentic workflows, embeddings, vector search, prompt design and model evaluation.
• Hands-on exposure to major cloud AI platforms such as Azure OpenAI, Google Vertex AI or AWS Bedrock.
• Strong understanding of APIs, data pipelines, event-driven integration and how AI services integrate with existing enterprise applications.
• Experience leading multidisciplinary engineering, platform, DevOps or infrastructure teams.
• Track record of application modernisation or technology transformation, particularly where legacy and modern systems need to coexist.

Why you should join them

This is an opportunity to build an AI engineering capability from the ground up within an established regional technology business. The groundwork already exists, but the next phase is about taking that work into production and embedding AI into real products and operations.

Unlike many senior AI positions centred primarily on strategy or governance, this role combines building, modernising and leading. The successful candidate will have direct ownership of the technology, an existing platform organisation to lead and the mandate to establish the company's internal AI engineering capability.

Reporting directly to the CEO, they will have significant influence over how the company's technology estate evolves and how Generative AI is applied across its products in the years ahead.