Join the team leading the next evolution of virtual care.
At Teladoc Health, you are empowered to bring your true self to work while helping millions of people live their healthiest lives.
Here you will be part of a high-performance culture where colleagues embrace challenges, drive transformative solutions, and create opportunities for growth. Together, we’re transforming how better health happens.
Summary of Position
We are seeking a Principal II Data & AI Platform Engineer to serve as one of the most senior hands-on technical leaders on our Data & AI Platform team. This role will architect, build, and scale production generative AI applications and agentic systems, including member-facing experiences. You will drive technical decisions for AI architecture, agent infrastructure, and integration with our Databricks ecosystem while directly contributing to design and implementation.
The ideal candidate brings a strong foundation in traditional machine learning and deep learning, followed by substantial recent experience engineering production GenAI solutions. This is a highly influential individual contributor role with technical decision-making authority, cross-team leadership, and an opportunity to shape how Teladoc delivers reliable, secure AI at scale.
Essential Duties and Responsibilities
Lead the architecture and hands-on development of production GenAI applications, including member-facing AI agents, conversational experiences, and API-based workflows.
Design and build reusable agent infrastructure, including orchestration, tool/function calling (such as MCP), RAG, vector search, context management, and model integrations.
Architect AI solutions on Databricks, including platform integration, model serving, retrieval, and governance, with secure and reusable patterns for enterprise applications.
Make cross-team technical decisions on AI architecture, scalability, platform integrations, and build-versus-buy tradeoffs, while remaining accountable for implementation.
Establish production AI engineering practices for evaluation, automated testing, CI/CD, model/prompt versioning, observability, and troubleshooting.
Build safe, reliable AI systems with PHI/PII protections, guardrails, access controls, and performance and cost monitoring.
Partner with product, engineering, data, security, and compliance teams to deliver member-facing AI capabilities and integrate AI into enterprise applications.
Mentor engineers, set AI engineering standards, and communicate technical decisions to engineering leaders and executives while remaining deeply hands-on.
Participate in on-call support as a senior escalation resource for production AI incidents.
The time spent on each responsibility reflects an estimate and is subject to change dependent on business needs.
Supervisory Responsibilities
No
Qualifications Expected for Position
Bachelor’s degree in Computer Science, Engineering, Machine Learning, or a related field, or equivalent practical experience.
12+ years of experience building and running production systems (software, platform, or ML engineering). A proven record of setting technical direction for large, multi-team initiatives and defining architectures and standards used across the company.
5+ years of hands-on Databricks experience at production scale: Lakehouse architecture, Unity Catalog, Delta Lake
Spark/PySpark performance tuning
Workflows and Databricks SQL
Cost management (cluster policies, serverless compute)
Strong hands-on foundation in traditional machine learning or deep learning, predating widespread GenAI adoption, followed by recent, substantial agentic GenAI engineering experience.
Proven experience personally building, deploying, and operating production GenAI/LLM applications (ideally 3+ years), such as agentic APIs, workflows, or conversational products.
Strong knowledge of agent architecture, including orchestration, tool calling, RAG, vector retrieval, context management, evaluation, and observability.
Strong…