[Hiring] Principal II AI Platform Engineer @Teladoc Health

Role Description

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.

Qualifications

• 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, including Lakehouse architecture, Unity Catalog, Delta Lake, Spark/PySpark performance tuning, workflows, and Databricks SQL.
• Strong hands-on foundation in traditional machine learning or deep learning, 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 Python skills and experience delivering production AI services or APIs, with CI/CD, testing, monitoring, and operational troubleshooting.
• Ability to lead through technical authority, mentor engineers, collaborate across teams, and design secure, reliable systems while remaining a hands-on individual contributor.

Bonus Qualifications

• Hands-on experience with Databricks Mosaic AI, Unity Catalog, Delta Lake, MLflow, Vector Search, or Databricks Asset Bundles.
• Experience with Snowflake, dbt, Terraform, Spark/PySpark, or broader data lakehouse infrastructure.
• Experience with AI applications in healthcare or other regulated environments, including HIPAA or responsible AI frameworks.
• Familiarity with complementary AI/cloud frameworks and tools such as LangGraph, Semantic Kernel, Azure AI Foundry, Docker, or Kubernetes.
• Relevant Databricks or cloud AI certifications, open-source contributions, publications, or conference presentations.

Benefits

• Base salary range: $250,000 - $300,000.
• Eligible for performance bonus, RSUs, and benefits (subject to eligibility requirements).
• Flexible Vacation Policy for rest, relaxation, and personal time.
• 80 hours of Paid Sick, Safe, and Caregiver Leave annually.