AI Engineer

Description de l'entreprise

Within Publicis Groupe’s Intelligent Creativity business, we specialize in bringing creative ideas to life, and to consumers.

By combining 100 years of craft excellence with 6,000 experts across 52 locations of the world’s biggest studio network, we leverage the industry’s richest data, through the power of agentic AI, to radically redefine content production with Intelligent Content. We intuitively deliver this through Marcel Make, the world’s first Intelligent Content agent. The result? Predictively performing content that unlocks business growth in unprecedented ways.

No more guesswork. No more waste. Just content that works, working a lot harder.

The Publicis Production AI team leads innovation in generative AI, developing and deploying large language models (LLMs) and advanced AI technologies for business impact.

Descriptif du poste

We are looking for an AI Engineer to join the Publicis Production AI team and help build the next generation of AI-powered products and workflows for content and campaign creation. The engineer will join a multidisciplinary product team and work closely with AI engineers, software engineers, product managers, designers, and production specialists to turn emerging Generative AI capabilities into reliable, scalable products used by internal teams and clients.

The role is strongly hands‑on and combines backend engineering with applied AI. You will design and build scalable Python services and APIs using FastAPI, orchestrate large language, image, video, audio, and multimodal models, and develop innovative agentic and GenAI pipelines that automate or augment key stages of the campaign creation process. This includes workflows such as brief understanding, ideation, content generation, adaptation, quality checks, brand compliance, localization, and production automation.

You will work in a fast-moving environment where experimentation is important, but production quality matters equally. The objective is not only to prototype new AI capabilities, but to engineer them into secure, observable, maintainable services that can operate at scale across brands, markets, users, and production workflows.

Responsabilités

• Design, develop, and maintain scalable backend APIs and microservices in Python, primarily using FastAPI, to expose AI capabilities to Publicis Production products and internal platforms.
• Build orchestration layers that connect and manage multiple Generative AI models and providers, including LLMs, image generation, video generation, audio, embeddings, and multimodal models.
• Design and implement agentic workflows using modern orchestration patterns, including tool calling, structured outputs, state management, routing, retries, memory, and human-in-the-loop validation.
• Create innovative end-to-end GenAI pipelines for advertising and campaign creation, from brief interpretation and creative ideation through generation, adaptation, localization, validation, and production-ready outputs.
• Develop reusable AI components and services that can be integrated across multiple products, clients, markets, and use cases rather than building one-off prototypes.
• Integrate third‑party AI APIs and SDKs such as OpenAI, Google Gemini/Vertex AI, Adobe Firefly, Anthropic, and other emerging model providers, while abstracting provider‑specific implementation details where appropriate.
• Implement Retrieval‑Augmented Generation (RAG), embeddings, vector search, structured data retrieval, and grounding approaches when applications require access to brand, campaign, product, or operational knowledge.
• Evaluate models and prompting strategies for quality, latency, reliability, safety, and cost, and translate experimental findings into engineering decisions for production systems.
• Build robust data‑processing and asynchronous workflows for handling documents, images, video, and other creative assets at production scale.
• Implement production engineering best practices including automated testing, API validation, error handling, logging, monitoring, tracing, rate limiting, caching, and performance optimization.
• Deploy and operate AI services in cloud environments, primarily Azure and Google Cloud Platform (GCP), and contribute to CI/CD, containerization, configuration, secrets management, and production support.
• Collaborate with frontend, platform, DevOps, product, and data teams to define technical solutions and integrate AI services into user‑facing products.
• Participate actively in agile product delivery through technical design, sprint planning, code reviews, pull requests, documentation, troubleshooting, and continuous improvement.
• Stay current with rapidly evolving Generative AI technologies, test new models and frameworks, and identify opportunities to turn promising