Senior LLMOps/MLOps Engineer — Multi-Cloud CI/CD

Sedgwick; Santa Fe (NM); On-site; USD 100,000 - 130,000; Full time

Job summary

A leading AI innovation company in Santa Fe, New Mexico is seeking an experienced engineer to manage the production lifecycle of AI initiatives. This role focuses on building automated infrastructure that connects legacy systems with modern AI services on AWS and Azure. Candidates should possess 6+ years of engineering experience, especially in MLOps, with strong skills in Python, SQL, and Azure services. This is a critical role for ensuring the scalability and observability of AI applications.

Qualifications

• Bachelor’s degree in Computer Science or a related field required; Master’s degree in a quantitative discipline highly desirable.
• 6+ years of engineering experience, minimum of 3 years focused on MLOps or LLMOps in production.
• Deep proficiency in AWS and Azure ecosystems, including configuring services and networking.
• Expert in Python, SQL, PySpark; experience with Docker, Kubernetes, and orchestration tools.
• Experience with evaluation and observability frameworks like LangSmith or WhyLabs.

Responsibilities

• Build and maintain CI/CD and CT pipelines across AWS and Azure.
• Design infrastructure for Retrieval-Augmented Generation (RAG) and optimize database management.
• Build pipelines to ingest and move data into cloud-native MLOps workflows.
• Deploy monitoring for model drift and manage quality and cost.
• Partner with teams to ensure high-fidelity data flow between analytics and production.

Skills

MLOps

AWS

Azure

Python

SQL

PySpark

Docker

Kubernetes

Airflow

Statistical validation

Education

Bachelor’s degree in Computer Science or related field

Master’s degree in quantitative discipline

Tools

Terraform

CloudFormation

LangSmith

Arize Phoenix

WhyLabs

OpenSearch

Pinecone

Databricks

Snowflake

Job description

A leading AI innovation company in Santa Fe, New Mexico is seeking an experienced engineer to manage the production lifecycle of AI initiatives. This role focuses on building automated infrastructure that connects legacy systems with modern AI services on AWS and Azure. Candidates should possess 6+ years of engineering experience, especially in MLOps, with strong skills in Python, SQL, and Azure services. This is a critical role for ensuring the scalability and observability of AI applications.