Lead AI Engineer

Overview In this role you will design and deliver enterprise AI applications that integrate with existing systems, building scalable AI architectures and agentic patterns to automate data-driven workflows. You will collaborate with cross-functional teams to identify AI opportunities and mentor others on AI engineering practices. You will work across Supply Chain, ROP, Call Center, and Operations to advance business outcomes through AI-enabled solutions. This is a hands-on, production-focused role that combines cloud architectures, data engineering, and bleeding-edge AI tooling to drive real business impact. Compensation / Benefits Medical, Dental, Vision coverage Paid Time Off Retirement Benefitscomplimentary Health Screenings Responsibilities Design, develop, test, and deploy enterprise AI applications and services Build scalable architectures integrating AI into business systems and workflows Create agentic AI patterns for reasoning, data retrieval, workflow triggers, and business actions Define reusable agent frameworks for priority use cases across supply chain, ROP, call center, and operations Mentor developers, analysts, and technical team members on AI engineering best practices Collaborate with business stakeholders to identify AI opportunities and challenges Contribute to other projects or duties as assigned Key requirements Bachelor's degree in CS, Engineering, Data Science, IT or related field with 4–6 years of software/data/AI experience, or GED with 7+ years of relevant experience 3+ years of hands-on production AI/ML implementation experience Experience designing enterprise-scale applications and cloud architectures Proficiency in Python, SQL, REST APIs, Git, and Dev Ops practices Experience with ML frameworks (Tensor Flow, PyTorch, scikit-learn) and large language models (OpenAI, Azure OpenAI, Anthropic, Gemini, etc.)Experience with Prompt Engineering and Retrieval-Augmented Generation (RAG)Familiarity with vector databases, cloud platforms (Azure, AWS, GCP), CI/CD, data modeling and data engineering fundamentals Experience with Microsoft Graph API, Cosmos DB or equivalent vector/operational stores, Git Hub Copilot, Snowflake or similar data platforms Preferred tools: Azure AI Foundry, Microsoft Copilot Studio, Microsoft Fabric, Snowflake, Databricks, Lang Chain, Semantic Kernel, Docker, Kubernetes, MLflow, Llama Index, Agent Frameworks and Autonomous AI Systems Collaborative mindset Strong communication with stakeholders Mentorship and coaching abilities PythonSQLREST APIs