AI Engineer

INFINEUM SINGAPORE LLP; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

INFINEUM SINGAPORE LLP is seeking a seasoned AI Agent Engineer to join our Data and Analytics team in Singapore. You will drive the end-to-end lifecycle of AI agents, from concept to production, leveraging agent frameworks and LLM-powered automation to unlock business value.

You will guide stakeholders, ensure secure and scalable deployments, and stay at the forefront of AI tooling and enterprise AI operations.

Qualifications

• Hands-on experience building AI agents end-to-end using agent or LLM frameworks.
• Experience with MCP servers or similar systems enabling agent interaction with external apps.
• Ability to guide multi-stakeholder projects and communicate solution direction.
• Proficiency in Python and Git, plus CI/CD workflows.

Responsibilities

• Collaborate with cross-functional teams to ensure projects deliver meaningful business impact.
• Manage the full agent lifecycle: delivery, quality, and continuous improvement.
• Act as technical lead when delivering internal agent projects with partners.
• Support business units using Copilot Studio by sharing best practices for AI agents.
• Stay updated with agent frameworks, AI tooling, and LLM technologies to code custom AI agents.
• Deploy agents into production ensuring robustness, security, and scalability.
• Develop semantic descriptions of SQL schemas and MCP-based tooling for legacy access.
• Identify opportunities to develop and integrate AI agents that convert data into actionable insights.

Skills

Python

Git

Azure DevOps

CI/CD tooling

Agent frameworks

Stakeholder guidance

Technical leadership

Azure AI Foundry

Azure OpenAI

Copilot Studio

Microsoft Agent Framework

LangGraph

LangChain

Secure integration

Education

Master’s degree in Computer Science or related field

Tools

MCP servers

Copilot Studio

Azure cloud services

Job description

Position Summary:

Join our Data and Analytics team to be at the forefront of bringing AI Agents from concept to production, enabling teams across Infineum to turn ideas into real, measurable impact. Apply cutting-edge agent frameworks and LLM-powered automation to solve real business problems at scale, accelerating digitalisation across our global organisation.

In this role, contribute how our data, systems, and applications become “AI-ready.” Guide business stakeholders from a spark of inspiration to deployed agent solutions that streamline workflows, amplify expertise, and unlock new value. Whether you’re governing the lifecycle of an agent, refining its behaviour, or deploying it into production environment, you’ll be the technical force ensuring our agents are safe, reliable, and truly helpful.

If you’re excited about building and operationalising AI agents, collaborating across functions, and making AI real for hundreds of users, this role offers the perfect platform to grow, innovate, and see your work drive impact.

Key Responsibilities / What You'll Achieve

• Collaborate with cross-functional teams to ensure projects deliver meaningful business impact.
• Manage the full agent lifecycle, ensuring timely delivery, quality, and continuous improvement.
• Act as a technical lead when working with partners to deliver internal agent-related projects.
• Support business functions, which use our no-code agent platform (Copilot Studio), by providing expertise and best practices in AI agents and their practical applications.
• Stay current with state-of-the-art developments in agent frameworks, AI tooling, and LLM technologies to code custom-built AI agents.
• Deploy agents into production environments, ensuring they are robust, secure, and scalable.
• Contribute to best practices that make enterprise data AI-ready - for example, helping craft semantic descriptions of SQL schemas and developing MCP-based tooling for agent access to legacy applications.
• Help to identify opportunities for developing and integrating AI agents that convert data into actionable insights.

What will you gain from this role?

• Hands-on expertise in agent tech stacks - including frameworks such as Microsoft Agent Framework, LangGraph, GraphRAG with Neo4j, and MCP-based tooling that brings legacy systems into the world of intelligent automation.
• Experience the entire lifecycle of agent development, giving you the opportunity to take ideas from concept to production and directly see how your work improves the daily experience of colleagues across our business.
• Build both technical and non-technical strengths, from solution design and systems thinking to stakeholder communication, coaching business users, and driving adoption of agentic workflows.
• A collaborative, forward-looking team culture with a “can-do” mindset, where your ideas shape how Infineum harnesses AI agents and where you contribute to a growing community of agent builders transforming the organisation.
• Continuous learning as the field evolves rapidly, with access to cutting-edge tech stack, new frameworks, and enterprise AI operations practices.

Skills & Qualifications

Required:

• Demonstrated hands-on experience building AI agents end-to-end, from concept through to a functioning solution using any agent or LLM framework.
• Practical experience using agent tooling, including working with MCP servers or similar mechanisms that allow agents to interact with external systems.
• Ability to technically guide multi-stakeholder projects, showing that you can coordinate with partners, communicate clearly, and help shape solution direction.
• Strong proficiency in Python and comfort with version control tools such as Git.
• Exposure to Azure DevOps or equivalent CI/CD tooling, demonstrating familiarity with development and deployment workflows.

Preferred:

• Infineum has a Microsoft-first tech stack:
• Experience with Azurecloud services, including familiarity with AI-related offerings such as Azure AI Foundry and/or Azure OpenAI.
• Exposure to Microsoft no-code agent builder platform called Copilot Studio.
• Hands-on experience with Microsoft Agent Framework (or Auto Gen and Semantic Kernel), and/or LangGraph/LangChain, and an understanding of the limitations of each framework.
• Experience monitoring, evaluating, and improving custom built AI agents once deployed to production - e.g., evaluation, guardrail tuning, observability, or lifecycle governance.
• Familiarity with deploying and operating agents for business use, not just for testing, including secure connector usage and integration with legacy systems.
• A postgraduate degree (master’s or higher) in Computer Science, Life Science, Mathematics, or equivalent demonstrated experience in applied AI or data science.