AI Engineering Team Lead

Ambition; Hong Kong; On-site; HKD 1,200,000 - 1,800,000; Full time

Job summary

Ambition is seeking a hands-on AI Engineering Team Lead to build and scale enterprise AI products used by real business users. This role blends architecture, coding and leadership, requiring hands-on work on AI systems while guiding a team of engineers.

You will partner with stakeholders to translate business requirements into scalable AI solutions, drive technical decisions, and uphold engineering standards across platforms and workflows.

Qualifications

• 8-15 years of software engineering experience.
• Experience leading or mentoring engineering teams.
• Recent hands-on experience building and deploying production AI solutions.
• Strong understanding of AI agents, agent orchestration and enterprise AI architectures.
• Experience with Python, FastAPI, TypeScript/Node.js, cloud platforms (Azure, AWS or GCP), Docker and Kubernetes.
• Experience deploying solutions used by real business users in production environments.
• Excellent stakeholder management and communication skills.

Responsibilities

• Lead design, development and deployment of production AI applications and AI agent solutions.
• Mentor and support a team of AI and software engineers.
• Drive architecture decisions across AI platforms, agent orchestration and workflow automation.
• Partner with business stakeholders to translate requirements into technical solutions.
• Establish engineering standards, best practices and delivery processes.
• Oversee solution delivery from discovery and design through deployment and production support.
• Contribute hands-on to coding, troubleshooting and architectural reviews.

Skills

AI leadership

Team mentoring

Production AI

Python

FastAPI

TypeScript Node.js

Cloud platforms

Docker

Kubernetes

Stakeholder mgmt

Agent orchestration

LangGraph

MCP

RAG

Tools

LangGraph

MCP

RAG

Multi-Agent Systems

Job description

About the Role

We are looking for a hands-on AI Engineering Team Lead to help build and scale enterprise AI products used by real business users.

This is a technical leadership position for someone who enjoys both building production AI systems and leading engineers . You'll work closely with stakeholders to translate business requirements into scalable AI solutions while remaining actively involved in architecture, coding, code reviews and technical decision-making.

Responsibilities

• Lead the design, development and deployment of production AI applications and AI agent solutions
• Mentor and support a team of AI and software engineers
• Drive architecture decisions across AI platforms, agent orchestration and workflow automation
• Partner with business stakeholders to understand requirements and translate them into technical solutions
• Establish engineering standards, best practices and delivery processes
• Oversee solution delivery from discovery and design through deployment and production support
• Contribute hands-on to coding, troubleshooting and architectural reviews

Requirements

• 8-15 years of software engineering experience
• Experience leading or mentoring engineering teams
• Recent hands-on experience building and deploying production AI solutions
• Strong understanding of AI agents, agent orchestration and enterprise AI architectures
• Experience with technologies such as:
• LangGraph
• MCP (Model Context Protocol)
• RAG (Retrieval-Augmented Generation)
• Multi-Agent Systems
• Tool Calling / Function Calling
• LLM Evaluation and Guardrails
• Strong software engineering fundamentals with experience in:
• Python
• FastAPI
• TypeScript / Node.js
• Cloud platforms (Azure, AWS or GCP)
• Docker and Kubernetes
• Experience deploying solutions used by real business users in production environments
• Excellent stakeholder management and communication skills

What's Important

We're looking for a builder first .

The ideal candidate has personally designed and built AI solutions, understands production challenges, enjoys solving complex problems, and can provide technical leadership while remaining hands-on.

If you've successfully taken AI applications from concept to production and enjoy helping engineers grow, we'd love to hear from you.