Job Responsibilities

• Design and build a reusable multi-agent AI system that supports multiple projects and use cases

• Define agent roles, responsibilities, and interaction patterns, including planning, coordination, and task handoff

• Implement agent orchestration using frameworks such as LangChain, LangGraph, CrewAI, or similar

• Integrate self-hosted LLMs as well as commercial LLM APIs

• Develop backend services in Python, including:

  • Agent orchestration and execution logic

  • Tool integrations and external API access

  • Backend APIs for frontend consumption

• Develop and maintain frontend components using React.js, including:

  • User interfaces for interacting with AI agents

  • Visualisation of agent outputs and intermediate results

  • Human-in-the-loop workflows (review, approval, override)

• Implement agent evaluation and monitoring, covering:

  • Response quality and correctness

  • Performance and latency

  • Cost and resource usage

• Work closely with business users across departments to understand workflows and translate business needs into agent-based solutions

• Produce technical documentation, including system design, agent patterns, and usage guidelines

Job Requirements

• Diploma or higher qualification in Artificial Intelligence, Data Science, Computer Science, or a related field

• Strong hands-on experience in multi-agent AI system design and implementation

• Proficient in Python (backend) and React.js (frontend)

• Practical experience with LangChain, LangGraph, CrewAI, or similar AI agent frameworks

• Experience working with both self-hosted LLMs and commercial LLM services

• Familiarity with agent evaluation techniques and AI quality assessment

• Solid understanding of LLM limitations, including hallucinations and non-deterministic behavior

• Ability to design reliable AI systems with appropriate guardrails and human-in-the-loop controls

• Strong communication skills and ability to engage business users with varying technical backgrounds

• Able to work independently while collaborating closely with internal teams