ML Engineer

TEKsystems; Hong Kong; On-site; HKD 600,000 - 900,000; Full time

Job summary

TEKsystems Hong Kong is hiring for a growing AI team responsible for developing and scaling enterprise AI solutions that support business decisions across regions and functions. This role focuses on enhancing an existing AI platform, adapting it for different user groups and business requirements.

You will work across the full AI product lifecycle—from agent workflow design and backend development to deployment, monitoring, and production support—collaborating with frontend and cross‑functional

Qualifications

• 3+ years of experience in AI, machine learning, backend engineering, or a related field.
• Proven experience building and supporting production-grade applications.
• Strong Python development skills, including FastAPI and asynchronous programming.
• Hands-on experience with LangGraph and/or LangChain.
• Experience designing agent workflows, prompt engineering, and tool/function calling.
• Strong SQL skills, ideally with PostgreSQL, Databricks SQL, or similar platforms.
• Experience developing and integrating APIs.
• Good understanding of CI/CD pipelines, Docker, and production deployment practices.
• Experience with testing methodologies, including unit, integration, API, and performance testing.
• Knowledge of performance optimization, scalability, and distributed systems concepts.
• Experience with monitoring and observability tools such as Langfuse and Grafana.
• Ability to communicate in English and Chinese (Cantonese or Mandarin).
• Strong problem-solving skills and the ability to work effectively in a collaborative environment.

Responsibilities

• Collaborate with business stakeholders to understand requirements and translate them into AI-driven solutions.
• Design, build, and enhance AI agent workflows using existing frameworks and architectures.
• Develop and maintain backend services and APIs using Python and FastAPI.
• Integrate AI agents with internal data sources, databases, and external systems.
• Configure and adapt business logic, workflows, and data models to support multiple business teams and regions.
• Deploy, monitor, troubleshoot, and optimize AI applications in production environments.
• Implement testing strategies, including unit, integration, API, and performance testing.
• Improve system scalability and performance through caching, asynchronous processing, and latency optimization.
• Evaluate and enhance AI output quality, accuracy, explainability, and reliability.
• Monitor and mitigate hallucination risks while balancing response quality, performance, and cost.
• Work closely with frontend and cross-functional teams on API design and integration.
• Maintain observability and monitoring using modern logging and monitoring tools.

Skills

AI experience

Backend engineering

Python

Asynchronous programming

LangGraph LangChain

Agent workflows

Prompt engineering

Tool/function calling

SQL

PostgreSQL

APIs

CI/CD

Testing methodologies

Performance optimization

Distributed systems

Observability tools

English-Chinese communication

Tools

Python

FastAPI

PostgreSQL

Databricks SQL

Grafana

Langfuse

Docker

Job description

Join a growing AI team responsible for developing and scaling enterprise AI solutions that support business decision-making across multiple regions and functions. This role will focus on enhancing and expanding an existing AI platform, adapting it for different user groups, business requirements, and operational environments.

You will work across the full AI product lifecycle, from agent workflow design and backend development to deployment, performance optimization, monitoring, and production support.

Responsibilities

Collaborate with business stakeholders to understand requirements and translate them into AI-driven solutions.

Design, build, and enhance AI agent workflows using existing frameworks and architectures.

Develop and maintain backend services and APIs using Python and FastAPI.

Integrate AI agents with internal data sources, databases, and external systems.

Configure and adapt business logic, workflows, and data models to support multiple business teams and regions.

Deploy, monitor, troubleshoot, and optimize AI applications in production environments.

Implement testing strategies, including unit, integration, API, and performance testing.

Improve system scalability and performance through caching, asynchronous processing, and latency optimization.

Evaluate and enhance AI output quality, accuracy, explainability, and reliability.

Monitor and mitigate hallucination risks while balancing response quality, performance, and cost.

Work closely with frontend and cross-functional teams on API design and integration.

Maintain observability and monitoring using modern logging and monitoring tools.

Requirements

3+ years of experience in AI, machine learning, backend engineering, or a related field.

Proven experience building and supporting production-grade applications.

Strong Python development skills, including FastAPI and asynchronous programming.

Hands‑on experience with LangGraph and/or LangChain.

Experience designing agent workflows, prompt engineering, and tool/function calling.

Strong SQL skills, ideally with PostgreSQL, Databricks SQL, or similar platforms.

Experience developing and integrating APIs.

Good understanding of CI/CD pipelines, Docker, and production deployment practices.

Experience with testing methodologies, including unit, integration, API, and performance testing.

Knowledge of performance optimization, scalability, and distributed systems concepts.

Experience with monitoring and observability tools such as Langfuse and Grafana.

Ability to communicate in English and Chinese (Cantonese or Mandarin).

Strong problem‑solving skills and the ability to work effectively in a collaborative environment.