Senior GenAI Platform Engineer — Remote

Teladoc Health; Purchase (NY); On-site; USD 200,000 - 230,000; Full time

Benefits offered by this job

Flexible vacation policy

Paid sick leave (80 hours)

Caregiver leave

Inclusive benefits program

Job summary

The ideal candidate has 8+ years of AI/ML engineering experience with GenAI deployment, API-based AI services, large-scale data processing, and strong mentorship in tech direction. This role aims to drive innovation while ensuring reliability and governance in healthcare environments.

Qualifications

• 8+ years of AI/ML engineering experience with GenAI/LLM systems.
• Experience deploying LLM/GenAI solutions including RAG, vector DB, and agentic tool-augmented LLMs (LangChain, MCP, or similar).
• Experience with Snowflake or Databricks as core platforms for data processing or AI/ML workloads.
• Proven MLOps/LLMOps experience including CI/CD automation, model serving, monitoring, and governance with Docker, Kubernetes, Azure ML, MLflow, Terraform.
• Proficiency in Python and SQL; experience with Spark or other big data tools.
• Ability to collaborate across engineering, product, compliance, and security in regulated industries.

Responsibilities

• Operationalize GenAI and LLM apps with RAG, vector search, prompt engineering.
• Lead design, development, and deployment of production-grade LLM/ML pipelines (transformation, training, tuning, serving).
• Architect scalable AI workflows on Snowflake, Databricks, and Azure ML; integrate with data lakehouse platforms.
• Build API-based AI services (FastAPI, Flask) for secure, scalable model access.
• Define CI/CD pipelines using GitHub Actions/Azure DevOps, MLFlow; manage containers (Kubernetes, Docker).
• Develop and enforce MLOps/LLMOps practices: experiment tracking, versioning, observability, governance.
• Mentor ML engineers and data scientists on engineering rigor and production-readiness.
• Partner with cross-functional teams to integrate AI into products securely and compliantly.
• Troubleshoot production AI systems; analyze latency, drift, and performance; implement preventive solutions.
• Document architecture patterns and AI development frameworks across the organization.

Skills

GenAI deployment

LLM pipelines

API development

Snowflake

Databricks

MLOps/LLMOps

Kubernetes

Docker

Terraform

LangChain

FastAPI/Flask

Python

SQL

Big data tools (Spark)

Education

Bachelor's degree in Computer Science/Engineering/ML

Tools

Snowflake

Databricks

Azure ML

MLflow

Docker

Kubernetes

Terraform

LangChain

FastAPI/Flask

Job description

The ideal candidate has 8+ years of AI/ML engineering experience with GenAI deployment, API-based AI services, large-scale data processing, and strong mentorship in tech direction. This role aims to drive innovation while ensuring reliability and governance in healthcare environments.