Job Title Lead AI Engineer (Agentic AI Applications)
Location: Leawood, KS (Onsite)
Job Duration: Long Term Contract
Ideal Candidate Traits
Owns outcomes
- drives initiatives from concept to production with accountability and focus.
Thinks like a product builder
- connects engineering work to user and business value.
Strong in distributed systems and applied AI
- delivers scalable, production-ready solutions.
Acts with curiosity and bias for action
- proactive, self-directed, and solution-oriented.
Clarifies ambiguity
- asks the right questions and brings structure to complex problems.
Communicates with clarity and influence
across technical and product teams.
Passionate about impact
- builds intelligent, reliable systems that make a difference.
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.