AI Engineer

We are seeking a highly skilled and adaptable AI Engineer to join our development team in Leawood, KS. Whether you are a rising talent (Junior), an experienced specialist (Senior), or a strategic mentor (Lead), you will play a pivotal role in designing, building, and deploying production-grade AI solutions. You will work at the intersection of traditional backend engineering and cutting-edge Generative AI, leveraging Python, Azure, and LLM frameworks to build intelligent applications that solve complex business challenges., * LLM Application Development: Design and implement sophisticated AI workflows using LangChain or similar frameworks to integrate Large Language Models into enterprise applications.

• Backend & API Engineering: Build and maintain scalable, high-performance backend services and RESTful APIs to support AI-driven features.
• Cloud Architecture: Architect and manage cloud-based infrastructure within Azure, ensuring high availability and cost-effective scaling of AI services.
• Event-Driven Systems: Utilize Kafka to build responsive, real-time data streaming architectures and event-driven AI processes.
• Production Deployment: Take ownership of the full model lifecycle-from local experimentation to production-grade deployment and monitoring.
• MLOps & Pipelines: Establish and optimize data pipelines and MLOps practices to automate model training, testing, and versioning.
• Mentorship (Lead Level): Guide junior team members, set coding standards, and lead architectural reviews for AI/ML projects.

• Core Language: Strong, professional programming experience in Python.
• AI Frameworks: Hands-on experience with LangChain, LlamaIndex, or equivalent LLM orchestration tools.
• Cloud Platforms: Expertise in Azure services (Azure OpenAI, Azure Functions, Blob Storage, etc.) or equivalent cloud providers.
• Streaming & Messaging: Experience with Kafka or similar event-driven architectures.
• Development Fundamentals: Solid background in backend development, system design, and API security.
• Lifecycle Management: Proven experience deploying AI/ML models in live production environments and a deep understanding of MLOps principles.
• Data Engineering: Proficiency in building and managing robust data pipelines to feed AI models.