Principal II AI Platform Engineer, GenAI

Teladoc Health • Uniondale, NY

1d • $250,000 - $300,000 • Remote

About The Position

Teladoc Health is seeking a Principal II Data & AI Platform Engineer to serve as a senior hands-on technical leader on its Data & AI Platform team. The role will architect, build, and scale production generative AI applications and agentic systems, including member-facing experiences. The engineer will drive technical decisions for AI architecture, agent infrastructure, and integration with the Databricks ecosystem while contributing directly to design and implementation.

This influential individual-contributor position combines technical decision-making authority and cross-team leadership with hands-on engineering. The role calls for a foundation in traditional machine learning and deep learning alongside substantial recent experience building production GenAI solutions. It will shape how Teladoc delivers reliable, secure AI at scale and includes participation in on-call support as a senior escalation resource.

Requirements

• 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 in software, platform, or ML engineering.
• 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, Databricks SQL, and cost management such as cluster policies and 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 for 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.
• Currently authorized to work in the United States without requiring employment visa sponsorship or transfer now or in the future.

Nice To Haves

• 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.

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 and 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, using 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 and 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.

Benefits

• Performance bonus eligibility.
• RSUs.
• Benefits, subject to eligibility requirements.
• Flexible Vacation Policy; time off must be approved by the manager.
• 80 hours of Paid Sick, Safe, and Caregiver Leave annually for full-time positions.
• Inclusive benefits program with tailored programs for employees and their families.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal