Principal II AI Platform Engineer, GenAI
Teladoc Health2 days ago
Remote, United StatesStaff+
Base Salary
$250k - $300k/yr
Responsibilities
- Lead the architecture and hands-on development of production GenAI applications, member-facing AI agents, conversational experiences, and API-based workflows.
- Design and build reusable agent infrastructure covering orchestration, tool and function calling, retrieval-augmented generation, vector search, context management, and model integrations.
- Architect secure and reusable AI solutions on Databricks, including platform integration, model serving, retrieval, and governance.
- Set cross-team technical direction for AI architecture, scalability, platform integrations, build-versus-buy decisions, and enterprise standards while remaining accountable for implementation.
- Establish production AI engineering practices for evaluation, automated testing, deployment, model and prompt versioning, observability, troubleshooting, and performance and cost monitoring.
- Build reliable AI systems with PHI and PII protections, guardrails, access controls, and secure operational patterns.
- Partner with product, engineering, data, security, and compliance teams to deliver member-facing AI capabilities and integrate AI into enterprise applications.
- Mentor engineers, communicate technical decisions to engineering leaders and executives, and serve as a senior escalation resource during production AI incidents and on-call support.
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 software, platform, or ML engineering systems.
- 5+ years of hands-on production-scale Databricks experience, including Lakehouse architecture, Unity Catalog, Delta Lake, Spark/PySpark performance tuning, Workflows, Databricks SQL, and cost management.
- A proven record of setting technical direction for large, multi-team initiatives and defining architectures and standards used across a company.
- Strong foundation in traditional machine learning or deep learning followed by substantial recent agentic GenAI engineering experience.
- Proven experience personally building, deploying, and operating production GenAI or LLM applications, ideally for 3+ years.
- Strong knowledge of agent architecture, orchestration, tool calling, retrieval, vector retrieval, context management, evaluation, and observability.
- Strong Python skills and experience delivering production AI services or APIs with testing, monitoring, deployment, and operational troubleshooting.
- Ability to lead through technical authority, mentor engineers, collaborate across teams, and design secure and reliable systems as a hands-on individual contributor.
- Preferred qualifications include Databricks Mosaic AI, MLflow, Vector Search, Databricks Asset Bundles, Snowflake, dbt, Terraform, Spark/PySpark, data lakehouse infrastructure, healthcare or regulated-environment AI, HIPAA or responsible AI frameworks, LangGraph, Semantic Kernel, Azure AI Foundry, Docker, Kubernetes, relevant certifications, open-source contributions, publications, or conference presentations.
Benefits
- Flexible Vacation Policy.
- 80 hours of Paid Sick, Safe, and Caregiver Leave annually for full-time positions.
- Remote work arrangement indicated by the #LI-Remote designation.
- Eligible full-time employees may receive performance bonus, RSUs, and benefits subject to eligibility requirements.
Tech Stack
Categories
About Teladoc Health
Teladoc Health builds a virtual-care platform delivering primary, urgent, mental-health, and chronic-condition services via web and mobile, sold to employers, health plans, hospitals, and health systems. Its business model combines per‑member subscriptions with visit-based fees, supported by clinical networks and EMR integrations. The New York–based company is publicly traded on the NYSE and expanded its chronic-care capabilities by acquiring Livongo in 2020.