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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal II AI Platform Engineer, GenAI - **Company:** Teladoc, Inc. - **Location:** United States (Remote available) - **Experience:** Experienced - **Salary:** $250,000 - $300,000 - **Contract:** Permanent contract - **Skills:** LangGraph Framework, Application Programming Interfaces (APIs), Artificial Intelligence, Automation of Tests, Cloud Computing, Continuous Integration, Data Architecture, Information Retrieval, Python (Programming Language), Machine Learning, Performance Tuning, Search Technologies, Management of Software Versions, Enterprise Software Applications, Retrieval-Augmented Generation, Large Language Models, Snowflake, Apache Spark, IT Architecture, Deep Learning, Generative AI, Agentic-AI, Build Management, Data Lakes, AI Platforms, Pyspark, Kubernetes, Information Technology, Enterprise Integration, Free and Open-Source Software, Machine Learning Operations, Data Lakehouse, Api Design, Terraform, Semantic Kernel, Serverless Computing, Docker, Databricks - **Published:** November 12, 2026 - **Apply:** https://diversityjobs.com/career/18906108/Principal-Ii-Ai-Platform-Engineer-Genai ## About the Role 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., * 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 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., * 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. ## 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., * 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.