What will you do?

Technical Delivery

• Own end-to-end delivery of AI workstreams: from requirements through data preparation, modelling, integration, testing, and production handover
• Develop agentic applications including RAG pipelines, prompt-engineered agents, and agentic workflows using LangChain, LlamaIndex, LangGraph, or plain Python
• Build on top of GenAI application stacks including LLM orchestration, observability (Langfuse, Braintrust), guardrails, and LLM gateway patterns (LiteLLM, Portkey)
• Implement multi-agent orchestration layer: event routing, resource locking, inter-agent handoff contracts, prompt caching, and shared state management
• Implement agentic design patterns including workflow evaluation, LLM-as-Judge, and AI red teaming
• Adopt Model Context Protocol (MCP) and Agent-to-Agent (A2A) Protocol as foundational extension mechanisms, enabling agents to operate safel...