FLG -56 - Lead AI Engineer - Leawood, KS

Role : Lead AI Engineer

Location : Leawood, KS

Duration : Long Term

This is Lead AI position for a leading EDTECH Client in Leawood KS the position is onsite prefer candidates local but can consider relocation candidates (preferably for nearby Midwest - avoid coast to coast as they r always an issue)

The client feedback is shared here

Preferrable : No Data Scientists pls, mandate skills : AI, ML, Python / Java, Kafka, Data Engineering background with application development

• Led App Development teams and are aware of working with distributed systems
• Are well aware of architecture (backend) and integrations
• Taking Applications to production (so awareness of end to end working of systems)
• Preferably know Kafka
• Preferably worked as Data Engineering Leads
• Are tech savvy, have tried out building Gen AI apps.

Lead AI Engineer (Agentic AI Applications)

Location : Leawood, KS

Ideal Candidate Traits

Role Overview

Ascend Learning is seeking a Lead AI Engineer (Contract) who is a driver, not an order taker - someone who leads from the front, manages delivery across the AI team, and ensures successful execution of complex, high-impact AI initiatives.

You will architect and deliver applied AI solutions powered by Large Language Models (LLMs) and Small Language Models (SMLs) within a distributed, production-grade ecosystem .

This is a hands-on technical leadership and delivery management role that combines engineering excellence, team guidance, and cross-functional collaboration. You will work closely with Technical Product Owners (TPOs) , Technical Program Managers (TPMs) , Platform Engineering , and Senior Managers to deliver scalable, reliable, and innovative AI applications that transform digital learning experiences.

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.

Qualifications

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