Lead AI Engineer, Custom Solutions

Role Overview: You will be joining a leading experiential Media and Martech organization as an AI expert and innovator within a newly formed Centre of Excellence for Artificial Intelligence. Your role will involve designing, deploying, and scaling custom AI applications that have a direct impact on clients and internal efficiencies. This position offers a unique opportunity to be part of a global network solving pressing client challenges and setting the blueprint for AI innovation. Key Responsibilities: - Design, prototype, and deploy high-impact AI/ML models (e.g., marketing portfolio optimization, audience segmentation, content personalization) to deliver measurable business outcomes. - Architect and launch a Retrieval-Augmented Generation platform to increase knowledge accessibility and efficiency by at least 30%. - Collaborate with data teams to unify fragmented datasets and establish a scalable platform for cross-agency AI workflows. - Enhance and scale the AI-assisted Input Brief initiative into a network-wide capability with 50% agency adoption by year one. - Develop cloud-based, version-controlled AI pipelines to ensure model scalability, monitoring, and compliance with global data privacy standards. - Partner with global leadership to translate business challenges into AI-powered solutions and introduce innovations from emerging AI/ML research to the organization. Qualifications Required: - 8+ years of experience in software engineering/data science and 3+ years in applied AI/ML. - Hands-on experience building Retrieval-Augmented Generation (RAG) systems with frameworks like LangChain or LlamaIndex and vector databases like Pinecone or Chroma. - Proficiency in Python, TensorFlow, PyTorch, scikit-learn, and Hugging Face, with a strong grounding in NLP and unstructured text data. - Experience with at least one major cloud platform (AWS, GCP, Azure) for AI deployment. - Comfort with ambiguity and fragmented data, adept at turning messy inputs into structured insights. - Ability to design and manage complex AI workflows, including meta-agents, API integrations, and data transformations. - Skilled at communicating technical concepts clearly to non-technical stakeholders. - Familiarity with MLOps principles and tools like MLflow and Kubeflow is a plus. - Prior experience in marketing, advertising, or consulting environments is advantageous but not required.,