Teladoc Health is seeking an AI Engineer – Data & AI Platform to architect, build, and operationalize scalable GenAI and machine learning solutions across Snowflake, Databricks, and modern MLOps ecosystems. The role collaborates with data scientists, ML engineers, and platform teams to design and deploy end-to-end AI/ML pipelines, advance GenAI integration, and ensure production-grade reliability for AI-driven products.
Teladoc Health is seeking an AI Engineer – Data & AI Platform to architect, build, and operationalize scalable GenAI and machine learning solutions across Snowflake, Databricks, and modern MLOps ecosystems. The role collaborates with data scientists, ML engineers, and platform teams to design and deploy end-to-end AI/ML pipelines, advance GenAI integration, and ensure production-grade reliability for AI-driven products.
Key responsibilities: - Operationalize GenAI and LLM applications, including retrieval-augmented generation (RAG), vector search, prompt engineering, agentic AI, and Model Context Protocol (MCP). - Lead design, development, and deployment of production-grade LLM and ML pipelines (data transformation, feature engineering, training, tuning, serving). - Architect scalable data/AI workflows on Snowflake, Databricks, and Azure ML; integrate AI models with data lakehouse platforms. - Build and maintain API-based AI services (FastAPI, Flask) for secure, scalable model access. - Define and implement CI/CD pipelines for GenAI/ML services (GitHub Actions, Azure DevOps, MLFlow); manage containers with Kubernetes and Docker. - Develop robust MLOps/LLMOps practices: experiment tracking, model versioning, observability, governance. - Mentor ML engineers and data scientists; drive engineering excellence and production-readiness. - Partner with cross-functional teams to embed AI services into products while ensuring security, compliance, and resilience in regulated healthcare environments. - Troubleshoot production AI systems, address latency, drift, and performance issues
Track similar jobs
Get email alerts when new roles like this are posted.
Based on: Staff AI Engineer, GenAI
See how this role matches your resume
Sign in to get an AI match score and personalized feed.
Key responsibilities: - Operationalize GenAI and LLM applications, including retrieval-augmented generation (RAG), vector search, prompt engineering, agentic AI, and Model Context Protocol (MCP). - Lead design, development, and deployment of production-grade LLM and ML pipelines (data transformation, feature engineering, training, tuning, serving). - Architect scalable data/AI workflows on Snowflake, Databricks, and Azure ML; integrate AI models with data lakehouse platforms. - Build and maintain API-based AI services (FastAPI, Flask) for secure, scalable model access. - Define and implement CI/CD pipelines for GenAI/ML services (GitHub Actions, Azure DevOps, MLFlow); manage containers with Kubernetes and Docker. - Develop robust MLOps/LLMOps practices: experiment tracking, model versioning, observability, governance. - Mentor ML engineers and data scientists; drive engineering excellence and production-readiness. - Partner with cross-functional teams to embed AI services into products while ensuring security, compliance, and resilience in regulated healthcare environments. - Troubleshoot production AI systems, address latency, drift, and performance issues
Track similar jobs
Get email alerts when new roles like this are posted.
Based on: Staff AI Engineer, GenAI
See how this role matches your resume
Sign in to get an AI match score and personalized feed.
D365 Solutions Architect
Diversified
Senior Director, Customer Support
Dayforce
Senior Software Developer
Dayforce
Engineering Manager, Monetisation
Pet Media Group (PMG)
Strategic Account Executive
Optum
Strategic Account Executive
Optum
D365 Solutions Architect
Diversified
Senior Director, Customer Support
Dayforce
Senior Software Developer
Dayforce
Engineering Manager, Monetisation
Pet Media Group (PMG)
Strategic Account Executive
Optum
Strategic Account Executive
Optum
