Senior Leadership Role – AI Engineering & Platforms

Charterhouse Partnership; Singapore; On-site; SGD 280,000 - 420,000; Full time

Job summary

Charterhouse Partnership seeks a senior AI engineering and technology leader to build and scale enterprise AI capabilities across a large, complex organisation. You will own AI strategy, architecture and delivery of reusable AI platforms and services spanning ML, GenAI, Agentic AI, optimisation, digital twins and conversational AI.

This is a highly technical leadership role overseeing multidisciplinary teams across AI engineering, ML engineering, data science and applied AI, while remaining

Qualifications

• Significant experience leading AI/ML engineering organisations in complex enterprises.
• Strong technical depth across ML, GenAI, LLMs and Agentic AI.
• Experience building and scaling production AI platforms and services.

Responsibilities

• Define enterprise AI roadmap, architecture and standards.
• Build reusable AI platforms, services and frameworks across units.
• Lead multidisciplinary AI and engineering teams.
• Architect scalable AI agent solutions with orchestration, RAG, tools and memory.
• Establish MLOps, LLMOps and AgentOps practices and observability.
• Translate AI opportunities into measurable business outcomes.

Skills

AI leadership

ML engineering

GenAI

LLMs

Agentic AI

MLOps/LLMOps

System architecture

stakeholder management

communication to execs

commercial/product mindset

Job description

We are partnering with a large, complex organisation to appoint a senior AI engineering and technology leader to build and scale enterprise AI capabilities across the organisation.

The role will own the strategy, architecture and delivery of reusable AI platforms and services, spanning Machine Learning, Generative AI, Agentic AI, optimisation, digital twins and conversational AI.

This is a highly technical leadership role, overseeing multidisciplinary teams across AI engineering, ML engineering, data science and applied AI, while remaining involved in architecture and key technical decisions.

Key Responsibilities

AI Strategy & Architecture

• Define the enterprise AI roadmap, architecture and engineering standards.
• Build reusable AI platforms, services and frameworks across business units.
• Drive technology decisions across AI, data, models, agents and infrastructure.

AI Engineering Leadership

• Lead and develop multidisciplinary AI and engineering teams.
• Build capabilities across GenAI, Agentic AI, ML and emerging technologies.
• Foster technical excellence, innovation and continuous learning.

GenAI & Agentic AI

• Architect scalable AI agent solutions incorporating orchestration, RAG, tool use, memory and human oversight.
• Establish standards for LLM applications, evaluation, safety and observability.
• Drive the development of reusable components and enterprise AI patterns.
• Take AI initiatives from experimentation through to production and enterprise adoption.
• Drive improvements in reliability, performance, security, latency and cost.
• Oversee AI platforms and services throughout their lifecycle.

AI Operations & Governance

• Establish and mature MLOps, LLMOps and AgentOps practices.
• Build frameworks for evaluation, monitoring, observability and continuous improvement.
• Ensure responsible AI, security, privacy and regulatory requirements are embedded into AI delivery.
• Partner with technology, data, security, risk and business leaders to drive AI adoption.
• Prioritise AI investments based on business value, scalability and ROI.
• Shape build-vs-buy, technology and resource decisions.
• Translate technical opportunities into measurable business outcomes.

What We're Looking For

• Significant experience leading AI/ML engineering organisations in complex enterprises.
• Strong technical depth across ML, GenAI, LLMs and Agentic AI.
• Experience building and scaling production AI platforms and services.
• Strong understanding of AI agents, orchestration, RAG, tool use, evaluation and observability.
• Experience with MLOps, LLMOps and/or AgentOps.
• Proven track record taking AI from POC to production and enterprise scale.
• Strong architecture and software engineering fundamentals.
• Experience leading multidisciplinary teams and senior technical talent.
• Excellent stakeholder management and executive communication skills.
• Strong commercial and product mindset, with the ability to connect AI investment to business impact.