Artificial Intelligence Engineer

Key Performance Objectives

• Deliver client-ready AI solutions: Design, prototype, and deploy at least two high-impact AI/ML models (e.g., marketing portfolio optimization, audience segmentation, or content personalization) that deliver measurable business outcomes.

• Build scalable RAG systems: Architect and launch a Retrieval-Augmented Generation platform that enables global teams to intelligently query and apply decades of project data, increasing knowledge accessibility and efficiency by at least 30%.

• Break down data silos: Collaborate with data teams to unify fragmented, real-world datasets and establish a scalable platform that enables cross-agency AI workflows within the first year.

• Productize internal AI tools: Enhance and scale the “AI-assisted Input Brief” initiative into a network-wide capability with at least 50% agency adoption by year one.

• Establish secure, high-performance AI infrastructure: Develop cloud-based, version-controlled AI pipelines that ensure model scalability, monitoring, and compliance with global data privacy standards.

• Drive innovation and influence: Partner with global leadership to translate business challenges into AI-powered solutions, while introducing at least two new innovations from emerging AI/ML research to the organization.

Desired Qualifications

• Proven track record (4+ years in software engineering/data science; 2+ years in applied AI/ML) of designing and deploying production-ready AI solutions that deliver measurable impact.

• Demonstrated hands-on experience building modern Retrieval-Augmented Generation (RAG) systems with frameworks such as LangChain or LlamaIndex, and vector databases such as Pinecone or Chroma.

• Advanced proficiency in Python and core AI/ML libraries (TensorFlow, PyTorch, scikit-learn, Hugging Face) 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, actionable insights.

• Ability to design and manage complex AI workflows, including meta-agents, API integrations, and large-scale data transformations.

• Skilled at communicating complex technical concepts clearly to non-technical stakeholders.

• Experience with MLOps principles and tools (MLflow, Kubeflow) is a plus.

• Prior experience in marketing, advertising, or consulting environments is advantageous but not required.

What We Offer

• Opportunity to be a founding member of a high-visibility AI team.

• Direct impact on a global portfolio of iconic brands.

• A collaborative, innovative culture with room for experimentation and growth.

• Competitive salary and benefits package.