AI Full Stack Engineer

Company DescriptionRe:Sources is the backbone of Publicis Groupe, the world’s third-largest communications group. Formed in 1998 as a small team to service a few Publicis Groupe firms, Re:Sources has grown to 4,000+ people servicing a global network of prestigious advertising, public relations, media, healthcare and digital marketing agencies. We provide technology solutions and business services including finance, accounting, legal, benefits, procurement, tax, real estate, treasury and risk management to help Publicis Groupe agencies do what they do best: create and innovate for their clients. In addition to providing essential, everyday services to our agencies,Re:Sources develops and implements platforms, applications and tools to enhance productivity, encourage collaboration and enable professional and personal development. We continually transform to keep pace with our ever-changing communications industry and thrive on a spirit of innovation felt around the globe. With our support, Publicis Groupe agencies continue to create and deliver award-winning campaigns for their clients.OverviewPublicis Groupe is building a modern, scalable data and analytics ecosystem powered byAI-driven intelligence. We are seeking an AI Full Stack Engineer to design, develop, andintegrate end-to-end solutions that combine advanced machine learning capabilities withrobust, user-facing applications.This role sits at the intersection of AI/ML, software engineering, and data platforms,enabling the development of intelligent features that enhance data ingestion, discovery,automation, and insights across the platform.You will work closely with data engineers, UX designers, product teams, and DevOpsengineers to deliver scalable, high-performance solutions that bring AI into real userworkflowsResponsibilitiesAI & Machine Learning IntegrationDevelop, deploy, and maintain machine learning models within production environmentsBuild AI-driven features such as classification, anomaly detection, recommendation systems, and data enrichmentIntegrate AI/ML models into applications via APIs and microservicesMonitor, evaluate, and continuously improve model performance and reliabilityFull Stack DevelopmentDesign and build end-to-end features across front-end and backend systemsDevelop responsive, high-performance user interfaces using modern frameworks (e.g., React, Angular)Build and maintain scalable backend services and APIs supporting data workflowsEnsure seamless integration between UI components, AI services, and data pipelinesData Platform IntegrationWork with large-scale ETL pipelines and data processing systemsIntegrate applications with structured and semi-structured data sourcesCollaborate with data engineering teams to optimize data flows and performanceCloud, DevOps & ScalabilityDeploy applications and models in cloud environmentsContribute to CI/CD pipelines, automated testing, and DevOps best practicesEnsure scalability, security, and reliability of systemsWork with containerized applications and microservices architecturesCollaboration & Best PracticesPartner with UX teams to ensure AI outputs are intuitive and actionableParticipate in code reviews and enforce engineering standardsTroubleshoot and resolve issues across the full stackDocument solutions and contribute to knowledge sharingQualificationsBachelor’s degree in Computer Science, Engineering, Data Science, or related field4+ years of experience in software engineering, full stack development, or AI/ML engineeringStrong programming skills in Python and at least one backend language (Node.js, Java, .NET, Go.)Experience with machine learning frameworks (TensorFlow, PyTorch, scikit-learn)Experience with front-end frameworks (React, Angular, or similar)Experience designing and consuming RESTful APIsFamiliarity with ETL pipelines and data platformsExperience working with SQL and NoSQL databasesKnowledge of cloud platforms (AWS, Azure, or GCP)Experience with containerization (Docker, Kubernetes is a plus)Understanding of CI/CD pipelines and DevOps practicesStrong problem-solving, debugging, and analytical skillsFluent in EnglishPreferred QualificationsExperience building AI-powered features in production applicationsFamiliarity with Databricks, data warehouses, or BI toolsExperience with MLOps practices (model lifecycle management, monitoring, versioning)Exposure to LLMs, embeddings, or generative AI applicationsExperience with microservices architectureBackground working in data-intensive or analytics platforms