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Sobre este puesto de Principal Data & AI Platform Engineer, DataOps en Teladoc Health

Teladoc Health · Remoto · USA - Any Location (Remote)

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 context layers, semantic layers, model evaluation, or other patterns that make enterprise data more usable by AI systems.
  • Deep experience with data quality, data observability, lineage, fault tolerance, or automated remediation at scale.
  • Experience in healthcare or another regulated industry.

The base salary range for this position is $200,000 - $230,000. In addition to a base salary, this position is eligible for a performance bonus and benefits (subject to eligibility requirements) listed here: Teladoc Health Benefits 2026. Total compensation is based on several factors including, but not limited to, type of position, location, education level, work experience, and certifications. This information is applicable for all full-time positions.


#LI-SS2 #LI-Remote


We follow a Flexible Vacation Policy, intended for rest, relaxation, and personal time. All time off must be approved by your manager prior to use. You will also receive 80 hours of Paid Sick, Safe, and Caregiver Leave annually. This applies to full-time positions only. If you are applying for a part-time role, your recruiter can provide additional details.

As part of our hiring process, we verify identity and credentials, conduct interviews (live or video), and screen for fraud or misrepresentation. Applicants who falsify information will be disqualified.

 

Teladoc Health will not sponsor or transfer employment work visas for this position. Applicants must be currently authorized to work in the United States without the need for visa sponsorship now or in the future.

Why join Teladoc Health?

 

  • Teladoc Health is transforming how better health happens. Learn how when you join us in pursuit of our impactful mission. 

  • Chart your career path with meaningful opportunities that empower you to grow, lead, and make a difference.

  • Join a multi-faceted community that celebrates each colleague’s unique perspective and is focused on continually improving, each and every day.  

  • Contribute to an innovative culture where fresh ideas are valued as we increase access to care in new ways.   

  • Enjoy an inclusive benefits program centered around you and your family, with tailored programs that address your unique needs.

  • Explore candidate resources with tips and tricks from Teladoc Health recruiters and learn more about our company culture by exploring #TeamTeladocHealth on LinkedIn.

 

As an Equal Opportunity Employer, we never have and never will discriminate against any job candidate or employee due to age, race, religion, color, ethnicity, national origin, gender, gender identity/expression, sexual orientation, membership in an employee organization, medical condition, family history, genetic information, veteran status, marital status, parental status, or pregnancy). In our innovative and inclusive workplace, we prohibit discrimination and harassment of any kind.

Teladoc Health respects your privacy and is committed to maintaining the confidentiality and security of your personal information. In furtherance of your employment relationship with Teladoc Health, we collect personal information responsibly and in accordance with applicable data privacy laws, including but not limited to, the California Consumer Privacy Act (CCPA).  Personal information is defined as: Any information or set of information relating to you, including (a) all information that identifies you or could reasonably be used to identify you, and (b) all information that any applicable law treats as personal information. Teladoc Health’s Notice of Privacy Practices for U.S. Employees’ Personal information is available at this link.

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Cómo se compara este salario de DevOps

Este puesto paga $215,000/yr — por encima de el rango típico para los puestos de DevOps.

$107,500 la mediana de $175,000 $261,500

Rango típico $140,000–$214,775/yr, a partir de 2,080 ofertas comparables de DevOps en JobsRadar (salario anualizado en USD). Ver datos salariales de DevOps →

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