Lead AI Engineer
5 days ago
Location: Leawood, KS
Roles and Responsibilities:
- Delivery Management & Leadership: Manage delivery of AI engineering initiatives, ensuring projects are executed on time, within scope, and to high quality standards. Coordinate engineers and workstreams, resolve dependencies, and drive accountability.
- Technical Leadership & Team Guidance: Lead and mentor AI engineers in architecture, design, and implementation of best practices. Set engineering standards for quality, reliability, and maintainability.
- AI Solution Design & Development: Architect and develop Agentic AI applications using LLMs and SMLs for automation, reasoning, and content generation. Build distributed backend systems with Python, Fast API, Azure, Kafka, and Kubernetes.
- Cross-Functional Collaboration: Partner with Technical Product Owners, Technical Program Managers, and Platform Engineering to define scope, success metrics, and optimize infrastructure and performance.
- Innovation & Strategic Thinking: Stay current on advancements in LLMs, SMLs, RAG, and Agentic AI frameworks. Experiment with OpenAI and Azure AI tools and promote technical innovation balanced with predictable delivery.
- Productionization & Lifecycle Management: Lead productionization of AI application, ensuring reliability, observability, and lifecycle management of deployed solutions.
- Education & Experience: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a closely related field-or equivalent practical experience. Minimum of 7 years in software or AI engineering, with at least 2 years in technical leadership or architectural roles, demonstrating a proven track record of delivering complex solutions.
- Delivery Management Expertise: Demonstrated success managing end-to-end delivery for engineering teams or overseeing multi-stream technical projects, ensuring timely execution, high standards, and effective coordination across stakeholders.
- Technical Proficiency: Deep expertise in designing and implementing distributed systems, microservices architectures, and event-driven solutions. Hands-on experience with production-grade AI systems leveraging Large Language Models (LLMs) and Small Language Models (SMLs).
- Technology Stack Mastery: Advanced proficiency in Python, FastAPI, and Azure Cloud. Skilled in deploying and orchestrating solutions with Docker and Kubernetes. Familiarity with LangChain, LangGraph, vector databases, and Retrieval-Augmented Generation (RAG) pipelines.
- DevOps & Observability: Strong understanding of CI/CD pipelines, monitoring, logging, and tracing using tools like Datadog. Experienced with modern DevOps best practices to ensure system reliability and maintainability.
- Additional Competencies: Working knowledge of OpenAI APIs and the Azure ecosystem, including Cosmos DB, AI Search, and Cognitive Services. Familiarity with front-end frameworks (Angular, React) and principles of UI/UX design, enabling seamless integration of intelligent backends with web applications. Exceptional communication, collaboration, and leadership abilities, with a passion for mentoring teams and driving impactful results.
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