Teladoc

Staff AI Engineer, GenAI

Teladoc$200K — $230K *
US-AnywhereRemote in United States
Enterprise Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in Computer Science, Engineering, Machine Learning, or related field; equivalent experience accepted.
  • 8+ years of experience in AI/ML engineering with a focus on production LLM and GenAI systems.
  • Expertise in deploying LLM and GenAI solutions with frameworks like RAG and LangChain.
  • Experience with Snowflake and Databricks for data processing and AI/ML workloads.
  • Strong background in MLOps/LLMOps, including CI/CD automation and model governance.
  • Proficient in Python and SQL, with exposure to big-data processing using tools like Spark.
  • Ability to collaborate in cross-functional teams in regulated industries.

Responsibilities

  • Operationalize generative AI and LLM applications using advanced methodologies.
  • Lead the design and deployment of production-grade ML pipelines.
  • Architect scalable data workflows on platforms like Snowflake and Databricks.
  • Build and maintain API-based AI services for robust model access.
  • Define and implement CI/CD pipelines for ML services.
  • Enforce MLOps best practices including model tracking and governance.
  • Mentor engineers on scalable design and production-readiness.
  • Integrate AI services into products while ensuring compliance in healthcare contexts.
  • Troubleshoot production AI systems to optimize performance and reliability.
  • Document architecture patterns and operational standards for AI development.

Benefits

  • Flexible Vacation Policy for personal time.
  • 80 hours of Paid Sick, Safe, and Caregiver Leave annually.
  • Comprehensive health benefits offered to full-time employees.
Full Job Description
Summary of Position

We are seeking an AI Engineer - Data & AI Platform to architect, build, and operationalize scalable generative AI and machine learning solutions across Snowflake, Databricks, and modern MLOps ecosystems. This role will partner with data scientists, ML engineers, and platform teams to design and deploy end-to-end AI/ML pipelines, advance AI integration, and ensure production-grade reliability for AI-driven products.

The ideal candidate has 8+ years of experience in AI/ML engineering, with deep expertise in generative AI deployment, API-based AI services, large-scale data processing, and AI lifecycle management. The AI Engineer will not only deliver hands-on technical solutions but also set technical direction, mentor other engineers, and drive innovation across Teladoc's AI platforms.

Essential Duties and Responsibilities
  • Operationalize GenAI and LLM applications, leveraging RAG (retrieval-augmented generation), vector search, prompt engineering, agentic AI, and MCP (Model Context Protocol).
  • Lead the design, development, and deployment of production-grade LLM and ML pipelines, including data transformation, feature engineering, training, tuning, and serving.
  • Architect scalable data and AI workflows on Snowflake, Databricks, and Azure ML, integrating AI models with modern data lakehouse platforms.
  • Build and maintain API-based AI services (FastAPI, Flask), enabling secure, performant, and reliable model access at scale.
  • Define and implement CI/CD pipelines for GenAI and ML services, using GitHub Actions/Azure DevOps, MLFlow, and container orchestration (Kubernetes, Docker).
  • Develop and enforce MLOps/LLMOps best practices, including experiment tracking, model versioning, observability, and governance.
  • Mentor ML engineers and data scientists on engineering rigor, scalable design, and production-readiness.
  • Partner with cross-functional teams to integrate AI services into products, ensuring security, compliance, and resilience in regulated healthcare environments.
  • Troubleshoot production AI systems, analyzing inference latency, drift, and performance issues, and implementing preventive solutions.
  • Document and communicate architecture patterns, operational standards, and AI development frameworks across the organization.


The time spent on each responsibility reflects an estimate and is subject to change dependent on business needs.

Supervisory Responsibilities

No

Qualifications Expected for Position
  • Bachelor's degree in Computer Science, Engineering, Machine Learning, or a related field; equivalent work experience is acceptable.
  • 8+ years of experience in AI/ML engineering roles, with proven success in architecting and scaling production LLM/GenAI and ML systems.
  • Experience deploying LLM and GenAI solutions including RAG, vector database integration, and agentic/tool-augmented LLM systems (LangChain, MCP, or similar frameworks)
  • Experience with Snowflake or Databricks, using one or both as core platforms for data processing or AI/ML workloads.
  • Proven track record in MLOps/LLMOps, including CI/CD pipeline automation, model serving, monitoring, and governance, using modern AI infrastructure tools such as Docker, Kubernetes, Azure ML, MLflow, and Terraform.
  • Proficiency in Python and SQL, with experience processing high-volume datasets using big-data tools such as Spark or equivalent distributed systems.
  • Ability to collaborate in cross-disciplinary teams (engineering, product, compliance, security) and deliver impact in regulated industries.


Bonus Qualifications
  • Excellent communication skills to articulate complex GenAI/ML concepts to diverse audiences.
  • Strong leadership and mentorship abilities, fostering technical growth across teams.
  • Understanding of API-driven AI development, including Python-based API frameworks (FastAPI, Flask) or equivalent experience working with API development workflows.
  • Certifications in Snowflake, Databricks, Azure ML, or AI/ML platforms preferred.
  • Experience in healthcare AI applications and regulated AI deployment.


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.

About Teladoc

Teladoc Health, Inc. is a multinational telemedicine and virtual healthcare company that provides medical, behavioral health, and dermatological care services via phone, online video, and mobile apps. The company's platform connects patients with doctors and medical experts for virtual visits and consultations. Teladoc Health's services are available to individuals, employers, health plans, and health systems. The company was founded in 2002 and is headquartered in Purchase, New York.
Learn more about Teladoc
Size
5,100 employees
Market Cap
$3.8 billion
Industry
Net Income
-$485.1 million
Founded
2002
5 Year Trend
+75.2%
Revenue
$1 billion
NASDAQ

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