Senior Back-End Engineer AI

Job description

Company description Publicis Global Delivery (PGD); Publicis Groupe’s industry leading globally connected capability platform. Where talent, technology & operations combine to delivery amazing solutions for our clients. Expertise across Media, Data, Technology, Commerce & Production in all regions of the world. PGD is comprised of the best talent, and ways-of-working, which enables global scale, innovation and transformation, each day.

Culture, growth and wellbeing underline all aspects of Publicis Global Delivery. #WeArePGD Overview Come and be part of the team as one of the new Senior Backend Engineer focusing in AI.

Responsibilities

• Python expertise building and operating APIs/services, including:
• Designing and implementing RESTful APIs (or GraphQL where relevant)
• Python back-end frameworks such as FastAPI, Flask, or Django
• Deployment, monitoring, and maintenance in cloud/server environments (CI/CD, logs, metrics, tracing)
• Strong experience with data and persistence layers, including:
• Relational databases (PostgreSQL/MySQL/etc.), schema design, indexing, and query optimization
• Familiarity with vector search concepts and platforms (e.g., ChromaDB, Pinecone, Qdrant)
• Knowledge of caching and performance patterns (e.g., Redis) is a plus
• Solid understanding of software design principles (object-oriented design, modular architecture, design patterns) and building maintainable service-oriented systems
• Awareness with testing methodologies (unit/integration tests, contract testing) and engineering quality practices
• Awareness with cloud-based deployment (AWS, Azure, or GCP preferred), including containers/serverless where appropriate; infrastructure-as-code is a plus
• Proficiency with JSON and distributed-systems integration patterns; XML familiarity is a plus where legacy integrations exist

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent practical experience), with 1-3 years professional software engineering experience
• Proven experience delivering production-grade back-end services in small, cross-functional teams (agency/consultancy experience a plus) Additional information
• Experience working alongside data science, media, or ML teams
• Understanding of generative AI engineering and LLM system design, including:
• Practical knowledge of how LLMs behave (e.g., token limits/context windows, embeddings, latency/cost tradeoffs, hallucination risks)
• Experience integrating LLM providers and AI APIs (e.g., OpenAI/Azure OpenAI/Anthropic, or open-source models), including tool/function calling patterns and MCP
• Exposure to AI governance concepts such as bias awareness, explainability, or human-in-the-loop systems
• Comfort using generative AI tools (e.g., ChatGPT, Gemini, Claude) for development, ideation, or research
• Experience working with Docker containers and Kubernetes pods