Senior MLOps/LLMOps Engineer, Development

Citrin Cooperman

Senior MLOps/LLMOps Engineer at Citrin Cooperman developing automated pipelines for generative AI applications. Leading the deployment and management of AI evaluation infrastructure and monitoring.

Posted 6/30/2026full-timeRemote • 🇺🇸 United StatesSenior💰 $155,000 - $195,000 per yearWebsite

Tech Stack

Tools & technologies

AWSAzureCloudDockerKubernetesPython

About the role

Key responsibilities & impact

Design and build automated deployment pipelines specifically for generative AI applications
Ensure that updates can be safely promoted across environments (Dev, Test, Prod)
Deploy and manage the infrastructure required for continuous AI evaluation
Instrument AI applications to capture deep operational metrics
Implement version control for prompts and model configurations
Integrate input/output guardrails into the application flow to automatically block prompt injection attacks, PII leakage, or off-topic responses
Actively monitor the financial footprint of AI solutions

Requirements

What you’ll need

Bachelor’s degree in computer science, information technology, engineering, or equivalent practical experience
Databricks Certified: Machine Learning Professional
Microsoft Certified: Azure DevOps Engineer Expert (AZ-400)
DeepLearning.AI: Machine Learning Engineering for Production (MLOps)
4+ years of experience in DevOps, MLOps, or Site Reliability Engineering (SRE) with specific experience in generative AI deployments in last 1-2 years
Deep proficiency in building CI/CD pipelines using enterprise tools (Azure DevOps, GitHub Actions, GitLab CI)
Hands-on experience with LLMOps tools and frameworks (e.g., MLflow, LangSmith, PromptFlow, Arize, or similar observability platforms)
Strong Python scripting skills and experience containerizing machine learning or API workloads (Docker, Kubernetes)
Understanding of the API ecosystems for frontier models (OpenAI, Anthropic, Google Vertex AI) and multi-agent frameworks (LangChain, LangGraph)
Familiarity with cloud infrastructure (Azure, AWS) and infrastructure-as-code principles
Automation-obsessed
Financially vigilant
Analytical defender

Benefits

Comp & perks

Competitive compensation and benefits
Flexibility to manage personal and professional life

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

CI/CD Pipeline DevelopmentPython ScriptingContainerization (Docker, Kubernetes)Infrastructure ManagementVersion Control for AI ModelsOperational Metrics InstrumentationInput/Output Guardrails ImplementationFinancial Monitoring of AI SolutionsAutomation PrinciplesAPI Ecosystem Understanding

Soft Skills

Analytical DefenderFinancially VigilantAutomation-Obsessed

Certifications

Databricks Certified: Machine Learning ProfessionalMicrosoft Certified: Azure DevOps Engineer Expert (AZ-400)DeepLearning.AI: Machine Learning Engineering for Production (MLOps)