Principal Data & AI Platform Engineer, DataOps

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

As a Principal Data & AI Platform Engineer, you will architect, build, and operationalize AI-augmented capabilities that make our data platform more resilient, observable, scalable, and intelligent. This role focuses on DataOps - the systems that operate and support data pipelines rather than the pipelines themselves - including AI-driven monitoring, failure detection and recovery, data quality, and operational decisioning.

The ideal candidate combines deep data and software engineering experience with hands-on experience productionizing AI and agentic capabilities in engineering workflows. You will set technical direction, build solutions, lead cross-functional architecture and implementation efforts, and mentor engineers across the organization.

Essential Duties and Responsibilities

• Architect and implement AI and agentic capabilities that improve the reliability, scalability, and operational maturity of data processing systems.

• Build intelligent pipeline failure detection and recovery, including automated retry, root-cause assessment, escalation to on-call teams, and downstream user notification.

• Develop AI-driven data quality and heuristic monitoring to detect anomalies, assess impact, and recommend or automate the next best action.

• Design and evolve large-scale DataOps and platform capabilities that support enterprise data consumers and hundreds or more users.

• Productionize AI within data engineering operations with appropriate evaluation, observability, human review, and fallback paths.

• Partner with data engineering, platform, cloud, security, and business/data consumer teams to define requirements and drive technical solutions.

• Lead architecture and design reviews and establish reusable engineering patterns and standards for resilient data operations.

• Contribute hands-on to implementation, troubleshooting, and performance and scalability improvements across modern data platforms.

• Evaluate and apply modern data and AI technologies based on fit, scalability, reliability, and operational value.

• Mentor engineers and provide technical review and guidance on complex data platform and AI-enabled engineering problems.

Supervisory Responsibilities

No

Qualifications Expected for Position

• Bachelor's degree in Computer Science, Engineering, or a related field; equivalent work experience is acceptable.

• 10+ years of experience across data engineering, software engineering, or platform engineering, including senior-level architecture and large-scale system design.

• 3+ years of hands-on experience applying AI, GenAI, or agentic capabilities to data engineering, platform, or operational workflows.

• Proven experience architecting or engineering large-scale data processing systems serving a broad population of users or downstream consumers.

• Hands-on experience productionizing AI-augmented or agentic solutions, including evaluation, monitoring, failure handling, and operational support.

• Strong experience with modern data platforms such as Databricks or Snowflake and large-scale/distributed data processing patterns.

• Demonstrated ability to lead technical design and execution across teams, communicate with technical and business stakeholders, and influence without direct authority.

• Travel : Up to 10% Travel expectations are approximate and subject to change based on business needs.

Bonus Qualifications

• Experience with agentic AI and engineering frameworks such as Databricks Agent Bricks, LangChain, Hugging Face, or similar technologies.

• Experience with…