AI Engineer

Responsibilities

• 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, including:
• Agent orchestration and execution logic
• Tool integration 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 such as review, approval, and override
• Implement agent evaluation and monitoring mechanisms, covering:
• 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
• Able to work independently while collaborating closely with internal teams

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Company Intel

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