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
- 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: Bachelors or Masters 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
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)...
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
- 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: Bachelors or Masters 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
View more
View less