Senior AI & Cloud Engineer

Company description Starcom is the world's first standalone media agency, a storied innovator that continues to lead the way for many of the world's best brands. Starcom has long been the professional birthplace and proving ground for marketing leaders – CEOs, CMOs, sales leaders, and technology pioneers – and we continue to drive the industry with peerless talent and relentless innovation. From the start, we've known that achieving growth for our clients requires understanding and connecting with real people where they live and work, in ways they value. In an AI era, we remain ""Guided By Humanity,"" a phrase that describes our foundational belief that human expertise must remain in the driver's seat, supported by the best processes and technology. With our proprietary capabilities and Publicis Media's industry-leading resources and clout, we create ideas that move people and drive transformative business outcomes for brands. Overview We are looking for a Senior AI & Cloud Engineer to design, build, and operate intelligent data and AI systems on Azure. You will bridge the gap between cloud infrastructure, data engineering, and applied AI — developing production-grade pipelines and AI-assisted applications that create measurable business value. You will be a go-to voice on responsible AI practices, model selection, and evaluation within the team. Responsibilities Design and deploy scalable data and AI pipelines on Azure using Databricks, Azure Data Factory, and related services Build Retrieval-Augmented Generation (RAG) systems and AI-assisted workflows that integrate with internal data sources and APIs Develop and maintain Python-based applications, microservices, and Azure Container Apps Apply prompt engineering techniques and work with LLM APIs (OpenAI, Anthropic, Azure OpenAI) to deliver reliable, production-ready AI features Implement and maintain MCP (Model Context Protocol) integrations to connect AI models with enterprise tools and data sources Participate in fine-tuning and evaluation of models; contribute to model training workflows where applicable Establish best practices for AI observability, evaluation, safety guardrails, and responsible deployment Collaborate closely with data scientists, product managers, and business stakeholders to translate requirements into engineering solutions Mentor junior engineers and contribute to architectural decisions Qualifications 3+ years of hands-on software engineering experience, with at least 1 year focused on AI/ML systems in production Strong Python proficiency — data manipulation, API development, async patterns, testing Solid experience with Azure cloud services: Azure Data Lake, Azure Container Apps, Azure Blob Storage, Azure OpenAI Service, and related tooling Experience with Databricks for large-scale data processing and ML workflows (Delta Lake, Spark, MLflow) Practical experience with RAG architectures, vector databases (e.g. Azure AI Search, Chroma, Weaviate, pgvector), and embedding models Working knowledge of prompt engineering — few-shot prompting, chain-of-thought, system prompt design, output parsing Familiarity with Model Context Protocol (MCP) or equivalent tool-use / function-calling patterns in LLM applications Experience with Git-based version control and CI/CD pipelines (GitHub Actions, Azure DevOps) Additional information Starcom is an Equal Opportunity Employer. Our employment decisions are made without regard to actual or perceived race, color, ethnicity, religion, creed, sex, sexual orientation, gender, gender identity, gender expression, pregnancy, childbirth and related medical conditions, national origin, ancestry, citizenship status, age, disability, medical condition as defined by applicable state law, genetic information, marital status, military service and veteran status, or any other characteristic protected by applicable federal, state or local laws and ordinances. The Power of One starts with our people! To do powerful things, we offer powerful resources. Our best-in-class wellness and benefits offerings include: Paid Family Care for parents and caregivers for 12 weeks or more Monetary assistance and support for Adoption, Surrogacy and Fertility Monetary assistance and support for pet adoption Employee Assistance Programs and Health/Wellness/Comfort reimbursements to help you invest in your future and work/life balance Tuition Assistance Paid time off that includes Flexible Time off Vacation, Annual Sick Days, Volunteer Days, Holiday and Identity days, and more Matching Gifts programs Flexible working arrangements 'Work Your World’ Program encouraging employees to work from anywhere Publicis Groupe has an office for up to 6 weeks a year (based upon eligibility) Business Resource Groups that support multiple affinities and alliances The benefits offerings listed are available to U.S. based employees, are reviewed on an annual basis, and are governed by the terms of the applicable plan documents. 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. Compensation Range: USD $112,290.00 - USD $161,280.00/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 1/11/2027.

Design and deploy scalable data and AI pipelines on Azure using Databricks, Azure Data Factory, and related services Build Retrieval-Augmented Generation (RAG) systems and AI-assisted workflows that integrate with internal data sources and APIs Develop and maintain Python-based applications, microservices, and Azure Container Apps Apply prompt engineering techniques and work with LLM APIs (OpenAI, Anthropic, Azure OpenAI) to deliver reliable, production-ready AI features Implement and maintain MCP (Model Context Protocol) integrations to connect AI models with enterprise tools and data sources Participate in fine-tuning and evaluation of models; contribute to model training workflows where applicable Establish best practices for AI observability, evaluation, safety guardrails, and responsible deployment Collaborate closely with data scientists, product managers, and business stakeholders to translate requirements into engineering solutions Mentor junior engineers and contribute to architectural decisions

3+ years of hands-on software engineering experience, with at least 1 year focused on AI/ML systems in production Strong Python proficiency — data manipulation, API development, async patterns, testing Solid experience with Azure cloud services: Azure Data Lake, Azure Container Apps, Azure Blob Storage, Azure OpenAI Service, and related tooling Experience with Databricks for large-scale data processing and ML workflows (Delta Lake, Spark, MLflow) Practical experience with RAG architectures, vector databases (e.g. Azure AI Search, Chroma, Weaviate, pgvector), and embedding models Working knowledge of prompt engineering — few-shot prompting, chain-of-thought, system prompt design, output parsing Familiarity with Model Context Protocol (MCP) or equivalent tool-use / function-calling patterns in LLM applications Experience with Git-based version control and CI/CD pipelines (GitHub Actions, Azure DevOps)