AI Engineer

Unison Group; Singapore; On-site; SGD 90,000 - 170,000; Full time

Job summary

Unison Group in Singapore is seeking engineers to design, build, and deploy AI agents and end-to-end agentic AI solutions that address complex problems across technical and manufacturing domains.

You will work with domain PhDs to translate complex processes into practical AI workflows, develop agentic solutions using LangGraph, LangChain, Semantic Kernel, and integrate agents with enterprise systems for real-world task execution and decision-making.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related field.
• Strong programming skills in Python with hands-on experience developing production-grade AI applications.
• Proven hands-on experience building and deploying Agentic AI systems in real-world production environments.
• Strong experience with agent frameworks such as LangGraph, LangChain, Semantic Kernel, or equivalent frameworks, with a deep understanding of agent orchestration and workflow design.
• Direct experience developing multi-agent systems, tool-calling agents, autonomous/semiautonomous workflows, RAG-based agents, agent memory, and agent-to-agent interactions.
• Experience designing and implementing real-world agent workflows involving tool integration, API calls, decision-making, planning, state management, human-in-the-loop processes, and workflow orchestration.
• Experience building LLM-based applications and integrating LLMs with enterprise data, APIs, databases, and external tools.
• Ability to work closely with technical domain experts and translate specialized scientific/process knowledge into effective agentic systems.
• Strong analytical, problem-solving, and process-mapping skills, with the ability to understand and work across unfamiliar technical domains.
• Experience deploying, monitoring, evaluating, and optimizing production agentic AI systems, including observability, reliability, security, governance, and MLOps practices.

Responsibilities

• Design, build, and deploy AI agents and agentic AI solutions across technical and manufacturing domains.
• Collaborate with domain PhDs to translate processes into practical AI workflows.
• Develop agentic AI solutions using LangGraph, LangChain, Semantic Kernel, or other frameworks.
• Integrate agents with enterprise systems, APIs, databases, and tools for real-world task execution and decision-making.
• Deploy, monitor, troubleshoot, and optimize agentic AI solutions in production with security, governance, and scalability.

Skills

Python programming

Multi-agent systems

Workflow orchestration

Analytical skills

Problem solving

Education

Bachelor's degree in Computer Science or Engineering

Tools

LangGraph

LangChain

Semantic Kernel

Job description

• Design, build, and deploy AI agents and end-to-end agentic AI solutions that solve complex problems across multiple technical and manufacturing domains


• Work directly with domain PhDs and subject-matter experts to understand, document, and translate complex scientific and manufacturing processes into practical AI workflows


• Translate domain expertise and process knowledge into structured workflows, agent architectures, tools, models, and production-ready agentic systems


• Develop agentic AI solutions using frameworks such as LangGraph, LangChain, Semantic Kernel, or other agent orchestration frameworks


• Build multi-agent workflows, RAG pipelines, tool-calling agents, memory-enabled agents, and autonomous/semiautonomous workflows grounded in real-world domain knowledge


• Integrate agents with enterprise systems, APIs, databases, and specialized tools to enable real-world task execution and decision-making


• Deploy, monitor, troubleshoot, and continuously optimize agentic AI solutions in production, with appropriate security, governance, reliability, and scalability

• Design, build, and deploy AI agents and end-to-end agentic AI solutions that solve complex problems across multiple technical and manufacturing domains


• Work directly with domain PhDs and subject-matter experts to understand, document, and translate complex scientific and manufacturing processes into practical AI workflows


• Translate domain expertise and process knowledge into structured workflows, agent architectures, tools, models, and production-ready agentic systems


• Develop agentic AI solutions using frameworks such as LangGraph, LangChain, Semantic Kernel, or other agent orchestration frameworks


• Build multi-agent workflows, RAG pipelines, tool-calling agents, memory-enabled agents, and autonomous/semiautonomous workflows grounded in real-world domain knowledge


• Integrate agents with enterprise systems, APIs, databases, and specialized tools to enable real-world task execution and decision-making


• Deploy, monitor, troubleshoot, and continuously optimize agentic AI solutions in production, with appropriate security, governance, reliability, and scalability

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related field


• Strong programming skills in Python with hands-on experience developing production-grade AI applications


• Proven hands-on experience building and deploying Agentic AI systems in real-world production environments


• Strong experience with agent frameworks such as LangGraph, LangChain, Semantic Kernel, or equivalent frameworks, with a deep understanding of agent orchestration and workflow design


• Direct experience developing multi-agent systems, tool-calling agents, autonomous/semiautonomous workflows, RAG-based agents, agent memory, and agent-to-agent interactions


• Experience designing and implementing real-world agent workflows involving tool integration, API calls, decision-making, planning, state management, human-in-the-loop processes, and workflow orchestration


• Experience building LLM-based applications and integrating LLMs with enterprise data, APIs, databases, and external tools


• Ability to work closely with technical domain experts and translate specialized scientific/process knowledge into effective agentic systems


• Strong analytical, problem-solving, and process-mapping skills, with the ability to understand and work across unfamiliar technical domains


• Experience deploying, monitoring, evaluating, and optimizing production agentic AI systems, including observability, reliability, security, governance, and MLOps practices