AI, Content Intelligence EngineerPublicis Groupe Holdings B.V • New York, New York, United States
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AI, Content Intelligence Engineer
Publicis Groupe Holdings B.V
- New York, New York, United States
- New York, New York, United States
Über
Design and develop end‑to‑end AI‑powered services for content production workflows. Build modular components (APIs, services) that integrate with enterprise platforms. Leverage LLMs, RAG pipelines, diffusion models, and vector databases. Ensure systems are extensible, reusable, and production‑safe. Build modular, extensible systems using Infrastructure as Code (e.g. Terraform) to enable repeatable environments, scalable architecture, and seamless service integration. Rapidly prototype capabilities to validate feasibility. Evolve prototypes into MVP tools with real operator usage. Productionize systems with scalability, reliability, and workflow integration. Build AI‑assisted generation pipelines and content optimization tools. Develop reusable, modular capabilities that scale across clients. Enable self‑service and assisted creation models for operators. Engineer systems that convert data and performance signals into actionable inputs, e.g. integrated content recommendation engine. Guide content creation, adaptation, and optimization decisions. Integrate solutions into production environments including workflow and DAM systems. Ensure outputs are telemetry‑driven, traceable, governed, and compliant across systems and workflows. Design and implement CI/CD pipelines (e.g. Git‑based workflows) to support automated build, test, and deployment for reliable, continuous delivery. Build systems that adhere to secure data handling and enterprise security standards. Ensure observability, monitoring, and auditability of systems.
Qualifications
7-10+ years in software engineering, AI/ML engineering, or related fields. 2-5+ years of experience in content production‑grade software. Strong Python proficiency and experience with modern AI/ML frameworks. Experience building and deploying production‑grade systems. Familiarity with LLMs, RAG, generative models, and cloud‑native architectures. Experience with APIs, microservices, and system integration. Ability to translate complex requirements into scalable engineering solutions. Strong collaboration skills across technical and non‑technical teams.
What Success Looks Like
PoCs consistently evolve into production tools used by operators. AI‑powered systems are embedded into content production workflows. Capabilities are delivered as reusable, scalable services. The organization operates as a product‑building engine, not just strategy. AI becomes infrastructure within production, not experimentation.
Technical Competencies
Python, APIs, modular system architecture (microservices). LLMs, advanced prompt engineering system design, and RAG pipelines. Vector databases (e.g. Pinecone, FAISS) and data modeling (SQL). Generative AI systems (diffusion models, ComfyUI) and fine‑tuning methods (LoRA). Cloud platforms (GCP/AWS), Docker, Kubernetes, and Terraform (IaC). CI/CD pipelines (Git‑based workflows, automated build/test/deploy). Workflow orchestration and enterprise integrations (DAM, CMS, Workfront). Media processing pipelines (image/video/3D asset handling – e.g. GLB, OBJ, STL, CAD, RAW). Telemetry, logging, monitoring, and model evaluation/governance.
Benefits
Medical coverage, dental, vision, disability, 401k. Parental and family care leave, family forming assistance, tuition reimbursement. Flexible time off.
Compensation Compensation Range: USD $168,150.00 - USD $269,217.00 Annually. Additional Information If you require accommodation or assistance with the application or onboarding process specifically, please contact USMSTACompliance@publicis.com. All your information will be kept confidential according to EEO guidelines. Veterans Encouraged to Apply. #J-18808-Ljbffr
Sprachkenntnisse
- English
Hinweis für Nutzer
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