Director, AI Engineering

Company description Publicis Groupe is a global leader in communication and is positioned at every step of the value chain, from consulting to execution, combining marketing transformation and digital business transformation. Through a unified and fluid organization, Publicis Groupe partners with its clients across communication, media, data and technology to ensure access to the full breadth of capabilities in every market. Present in over 100 countries, Publicis Groupe employs around 103,000 professionals. Overview As Director, AI Engineering, you will own the technical architecture and hands-on build of AI agent and skill systems on the platform, turning complex business processes into scalable, production-grade AI engineering solutions. You will work at the intersection of deep technical execution and cross-functional leadership, guiding engineers through the design, development, and delivery of AI-native systems while setting the technical standards the broader organization builds against. Responsibilities Own the architecture and technical design of vertical-specific AI systems, translating business needs into scalable AI workflows, model integrations, and net-new engineering builds. Lead the hands-on design, development, and delivery of AI-native platform capabilities, from agent orchestration and retrieval pipelines to evaluation and monitoring frameworks. Set the technical approach for adapting existing engineering capabilities or architecting bespoke solutions to solve complex client and platform problems. Collaborate with Product, Strategy, Data Science, and Delivery to scope, price, structure, and prioritize technical proposals and engineering initiatives. Present technical architecture and live demos that map business challenges to engineering solutions, earning senior stakeholder and client confidence. Own the full software development lifecycle for AI systems, from design and prototyping through deployment, monitoring, and iteration. Serve as the senior technical voice in platform roadmap discussions, translating engineering feasibility and trade-offs into product direction and investment recommendations. Establish feedback loops across engineering and delivery teams to identify recurring technical challenges, guide platform enhancements, and prioritize scalable engineering investments. Mentor and provide technical leadership to engineers, guiding them through complex AI system design, debugging, and architectural decisions. Troubleshoot, debug, and optimize AI/ML systems and pipelines to improve performance, reliability, and cost efficiency. Develop internal enablement materials and technical narratives that equip teams to build and pitch AI solutions. Qualifications 8-12+ years of professional software engineering experience, with substantial recent focus on AI/ML systems (LLMs, agents, RAG, or applied AI platforms). Proven track record architecting and shipping production-grade AI-native systems at scale. Expertise in languages such as Python, Java, or TypeScript, and frameworks relevant to AI engineering (LangChain, LlamaIndex, PyTorch, or similar). Deep experience with cloud environments (AWS, Azure, or GCP) and modern data/ML infrastructure. Solid understanding of software design principles, distributed systems, algorithms, and data structures. Strong command of engineering best practices: version control, testing, CI/CD, and observability. Demonstrated ability to translate complex business or client needs into scalable technical architecture. Experience leading and developing engineering teams across co-located and virtual environments. Excellent communication skills, able to present technical concepts to both engineers and executive stakeholders. Experience building AI agent frameworks, tool/skill orchestration systems, or multi-agent architectures. Hands-on work with vector databases, embeddings, and retrieval-augmented generation (RAG) pipelines. Familiarity with LLM evaluation, fine-tuning, or prompt engineering at scale. Knowledge of microservices architecture and containerization (Docker, Kubernetes). Background in marketing technology, media data, or adjacent verticals. Active contributions to open-source AI/ML projects or a strong developer-community presence. Experience leading executive-facing technical demos or proof-of-concept work. Additional information Our Publicis Groupe motto “Viva La Différence” means we’re better together, and we believe that our differences make us stronger. It means we honor and celebrate all identities, across all facets of intersectionality, and it underpins all that we do as an organization. We are focused on fostering belonging and creating equitable & inclusive experiences for all talent. Publicis Groupe provides robust and inclusive benefit programs and policies to support the evolving and diverse needs of our talent and enable every person to grow and thrive. Our benefits package includes medical coverage, dental, vision, disability, 401K, as well as parental and family care leave, family forming assistance, tuition reimbursement, and flexible time off. If you require accommodation or assistance with the application or onboarding process specifically, please contact USMTTACompliance@publicis.com. All your information will be kept confidential according to EEO guidelines. Veterans Encouraged to Apply. #LI-MB5 Compensation Range: USD $135,375.00 - USD $216,684.00/Annually. This is the pay range the Company believes it will pay for this position at the time of this posting. Consistent with applicable law, compensation will be determined based on the skills, qualifications, and experience of the applicant along with the requirements of the position, and the Company reserves the right to modify this pay range at any time. Temporary roles may be eligible to participate in our freelancer/temporary employee medical plan through a third-party benefits administration system once certain criteria have been met. For regular roles, the Company will offer medical coverage, dental, vision, disability, 401k, and paid time off. The Company anticipates the application deadline for this job posting will be 12/11/2026.

Own the architecture and technical design of vertical-specific AI systems, translating business needs into scalable AI workflows, model integrations, and net-new engineering builds. Lead the hands-on design, development, and delivery of AI-native platform capabilities, from agent orchestration and retrieval pipelines to evaluation and monitoring frameworks. Set the technical approach for adapting existing engineering capabilities or architecting bespoke solutions to solve complex client and platform problems. Collaborate with Product, Strategy, Data Science, and Delivery to scope, price, structure, and prioritize technical proposals and engineering initiatives. Present technical architecture and live demos that map business challenges to engineering solutions, earning senior stakeholder and client confidence. Own the full software development lifecycle for AI systems, from design and prototyping through deployment, monitoring, and iteration. Serve as the senior technical voice in platform roadmap discussions, translating engineering feasibility and trade-offs into product direction and investment recommendations. Establish feedback loops across engineering and delivery teams to identify recurring technical challenges, guide platform enhancements, and prioritize scalable engineering investments. Mentor and provide technical leadership to engineers, guiding them through complex AI system design, debugging, and architectural decisions. Troubleshoot, debug, and optimize AI/ML systems and pipelines to improve performance, reliability, and cost efficiency. Develop internal enablement materials and technical narratives that equip teams to build and pitch AI solutions.

8-12+ years of professional software engineering experience, with substantial recent focus on AI/ML systems (LLMs, agents, RAG, or applied AI platforms). Proven track record architecting and shipping production-grade AI-native systems at scale. Expertise in languages such as Python, Java, or TypeScript, and frameworks relevant to AI engineering (LangChain, LlamaIndex, PyTorch, or similar). Deep experience with cloud environments (AWS, Azure, or GCP) and modern data/ML infrastructure. Solid understanding of software design principles, distributed systems, algorithms, and data structures. Strong command of engineering best practices: version control, testing, CI/CD, and observability. Demonstrated ability to translate complex business or client needs into scalable technical architecture. Experience leading and developing engineering teams across co-located and virtual environments. Excellent communication skills, able to present technical concepts to both engineers and executive stakeholders. Experience building AI agent frameworks, tool/skill orchestration systems, or multi-agent architectures. Hands-on work with vector databases, embeddings, and retrieval-augmented generation (RAG) pipelines. Familiarity with LLM evaluation, fine-tuning, or prompt engineering at scale. Knowledge of microservices architecture and containerization (Docker, Kubernetes). Background in marketing technology, media data, or adjacent verticals. Active contributions to open-source AI/ML projects or a strong developer-community presence. Experience leading executive-facing technical demos or proof-of-concept work.