Design and build a reusable multi-agent AI system that can support multiple projects and use cases
Define agent roles, responsibilities, and interaction patterns, including planning, coordination, and handoff
Implement agent orchestration using frameworks such as: LangChain, LangGraph, CrewAI
Integrate both self-hosted LLM models and commercial LLM services
Develop backend services in Python
Agent orchestration and execution logic
Tool integration and external API access
Backend APIs for frontend consumption
Develop and maintain frontend components using React.js,
User interfaces for interacting with AI agents
Visualisation of agent outputs and intermediate results
Human-in-the-loop workflows such as review, approval, and override
Implement agent evaluation and monitoring mechanisms
Response quality and correctness
Performance and latency
Cost and resource usage
Work with business users from different departments to understand requirements and workflows, and translate business problems into agent-based solutions
Produce technical documentation, including design documentation, agent patterns and usage guidelines

Requirements

Strong hands-on experience with multi-agent AI system design and implementation
Proficient in Python for backend development and React.js for frontend development
Practical experience using LangChain, LangGraph, CrewAI, or similar agent frameworks
Experience working with both self-hosted LLMs and commercial LLM APIs
Familiarity with agent evaluation approaches and AI quality assessment
Good understanding of LLM limitations, such as hallucinations and non-deterministic behaviour
Ability to design reliable systems with appropriate guardrails and human-in-the-loop controls
Strong communication skills and ability to engage business users with varying technical backgrounds

AI Engineer