Senior Agentic AI Engineer

Build multi-agent systems that turn data intelligence into automated, client-facing workflows. You will design and implement agentic architectures that make measurement models, data pipelines, and media optimisation tools accessible through natural interfaces. The goal: solutions that are cheap to build, cheap to run, and easy for non-technical teams to use.

Responsibilities:

• Design and build multi-agent systems using LLM orchestration frameworks (LangChain, LangGraph, CrewAI, or custom).
• Implement AI orchestration use cases for 4+ clients, focusing on low external dependency scenarios.
• Build agentic wrappers around existing data science models (MMM, forecasting, RBA, incrementality) so they can be queried and used conversationally.
• Set up and configure Genie spaces for client data exploration and self-service analytics.
• Develop tool-use patterns that connect agents to Databricks, Power BI, and other platform APIs.
• Write production-grade Python code with proper error handling, logging, and monitoring.
• Collaborate with Data Scientists to understand model inputs/outputs and build reliable agent interfaces.
• Participate in architecture reviews and contribute to the team's agentic design patterns and reusable components.

Requirements:

• 6+ years of software engineering experience with strong Python skills.
• 1+ year hands-on experience building with LLMs (prompt engineering, RAG, function calling, agent frameworks).
• Experience with at least one agent orchestration framework (LangChain, LangGraph, AutoGen, CrewAI).
• Understanding of API design, microservices, and event-driven architectures.
• Experience with cloud platforms (Azure preferred).
• Familiarity with vector databases, embeddings, and retrieval-augmented generation patterns.
• Strong debugging and problem-solving skills in distributed systems.