Applied AI Engineer

We are building a modern data and AI platform centered on Snowflake and a best-in-class data stack. As part of this effort, we are creating a living customer knowledge graph, one that evolves as customers interact with our platform and powers analytics, predictive models, recommendations, and AI-driven experiences throughout the Panacea app. 

We are seeking a Senior Applied AI Engineer to help design, build, and operationalize Panacea’s customer knowledge graph and applied AI capabilities. 

This is a senior, hands-on role that sits at the intersection of data engineering, analytics engineering, machine learning, and product development. You will work closely with the Data Engineering and Analytics Engineering on the Panacea Data Team and serve as a critical bridge between Platform Engineering, Product Management, and Business Leadership. 

You will guide how customer data, metadata, and relationships are modeled, curated, and activated, turning raw data into explainable, trustworthy AI systems that directly improve the customer experience.  

What You’ll Do

Knowledge Graph & Data Modeling 

• Design and evolve Panacea’s customer knowledge graph, modeling entities, relationships, events, and behaviors across the platform. 


• Define semantic data models that connect customer, product, behavioral, and financial data. 


• Curate and enrich metadata to ensure the knowledge graph remains accurate, explainable, and useful for analytics and AI. 


• Partner with the Data Engineering team to ensure source data is structured and modeled to support graph-based and AI use cases. 

Applied AI & Machine Learning 

• Develop and operationalize ML models that leverage the knowledge graph for: 
  
  
  
  • Predictive modeling 
  
  
  • Recommendations and personalization 
  
  
  • Risk and lifecycle insights 
  
  
  • AI-assisted customer experiences 
  
  


• Build and maintain pipelines for feature generation, training data creation, and model evaluation. 


• Support fine-tuning and integration of LLMs using internal data, metadata, and domain knowledge. 


• Help define guardrails, evaluation strategies, and explainability approaches for AI systems.

AI Enablement & Product Integration 

• Act as a technical partner to Platform Engineering and Product Management to integrate AI-driven capabilities into the Panacea app. 


• Translate business and product questions into data, graph, and AI solutions. 


• Help identify high-impact AI opportunities and guide them from concept to production. 


• Ensure AI solutions are scalable, maintainable, and aligned with regulatory and data governance requirements. 

Modern Data Stack & Tooling 

• Work within Panacea’s modern data stack, including: 
  
  
  
  • Snowflake as the cloud data warehouse 
  
  
  • dlt and Airbyte for data ingestion 
  
  
  • dbt for data transformations and modeling 
  
  
  • RudderStack for customer data and event collection 
  
  
  • PostHog for product analytics 
  
  
  • Lightdash for BI and exploration 
  
  
  • Hex for advanced analytics and data science 
  
  
  • Streamlit for internal data and AI applications 
  
  
  • DataHub for metadata management and data cataloging 
  
  


• Collaborate on standards for data quality, lineage, observability, and documentation.

• Serve as a technical thought leader for applied AI and knowledge graphs across the company. 


• Mentor team members and help raise the overall AI and data modeling maturity of the organization. 


• Communicate complex technical concepts clearly to technical and non-technical stakeholders. 


• Help establish best practices for responsible, explainable, and trustworthy AI at Panacea. 

Desired Skills & Experience

Core Experience 

• 6 years of experience across data engineering, analytics engineering, machine learning, or applied AI roles. 


• Strong hands-on experience with Python and modern data tooling. 


• Experience designing data models and semantic layers that support analytics and AI use cases. 


• Practical experience building and deploying ML models in production environments. 

AI & ML 

• Experience with supervised and unsupervised learning, feature engineering, and model evaluation. 


• Familiarity with LLM-based systems, including prompt engineering, retrieval-augmented generation (RAG), or fine-tuning. 


• Understanding of model lifecycle management, monitoring, and iteration. 

Data & Analytics 

• Strong SQL skills and experience working with cloud data warehouses (Snowflake preferred). 


• Experience with dbt or similar transformation frameworks. 


• Understanding of event-based data, behavioral analytics, and customer data platforms. 


• Comfort working with analytics and BI tools and partnering with analysts. 


• Experience with graph-based data modeling, knowledge graphs, or semantic technologies. 


• Familiarity with metadata management, data catalogs, and lineage concepts. 


• Experience connecting structured and semi-structured data into unified models. 

Collaboration & Communication 

• Proven ability to work across engineering, product, and business teams. 


• Comfortable operating in ambiguous problem spaces and shaping solutions. 


• Strong written and verbal communication skills. 

Qualifications 

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field (or equivalent experience). 


• Advanced degree or specialized AI/ML training is a plus. 


• Experience in fintech, SaaS, or regulated data environments is a plus. 


• Location: While this role allows for flexibility, we have a strong preference for candidates native to or based in Northeast Ohio.

Why This Role Matters 

This role will directly shape how Panacea understands its customers and how intelligence is embedded into our platform. You will help transform customer data into a living knowledgesystem that powers better decisions, better products, and better outcomes for the professionals we serve.