Senior AI & Cloud Engineer

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.

• 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)

3.53.5 out of 5 stars 35 West Wacker Drive, Chicago, IL 60601 $125,000 - $133,000 a year