MLOps / DevOps Engineer – AI Infrastructure

OpenKrill; United States; On-site; USD 130,000 - 170,000; Full time

Job summary

CreatorIQ is seeking a DevOps/ML Ops Engineer to support cloud and ML/AI infrastructure, automate deployments, and maintain CI/CD pipelines. This role emphasizes secure, scalable, and automated workflows across product and data science teams.

We value collaboration across time zones in a flexible, hybrid work model that combines in-person and remote work to boost innovation and operational excellence. Strong emphasis on IaC, monitoring, security, and reliability.

Qualifications

• 3+ years in DevOps, Cloud Engineering, SRE or similar.
• 2+ years supporting production ML/AI infrastructure.
• 2+ years with Databricks and/or AWS SageMaker.
• 2+ years AWS services (EC2, S3, RDS, Lambda, IAM, VPC).
• 2+ years with Kubernetes/EKS.
• Strong CI/CD experience with GitLab CI/CD or Jenkins.
• IaC experience with Terraform, Terragrunt, CloudFormation.
• Strong Linux administration and networking fundamentals.
• Scripting in Python or Bash for automation.

Responsibilities

• Maintain scalable, highly available, secure cloud infrastructure.
• Provision resources using IaC (Terraform, Terragrunt, CloudFormation).
• Implement cloud security best practices including IAM, encryption and vulnerability management.
• Support containerized environments and orchestration platforms.
• Apply DevSecOps practices across infra and deployment workflows.
• Participate in disaster recovery planning and testing.
• Maintain CI/CD pipelines and deployment automation for apps and ML models.
• Support AI/agentic infrastructure including MCP and integrations.
• Maintain monitoring and observability for infra and ML workloads.

Skills

DevOps

Cloud Engineering

SRE

CI/CD

Python scripting

Tools

Databricks

AWS SageMaker

AWS EC2

S3

RDS

Lambda

IAM

VPC

Kubernetes

EKS

GitLab CI/CD

Jenkins

Terraform

Terragrunt

CloudFormation

Job description

CreatorIQ is the operating system for creator-led growth trusted by more than 1,300 global brands and agencies.

We’re on a mission to make businesses more human, and humans more impactful. We operate by our values — be intentional, pursue excellence every day, embrace the journey together, and be a good human — every day. CreatorIQ has earned the title of best companies to work for in multiple programs, including BuiltIn LA and NY. It’s been named a Fastest-Growing Company in North America on the Deloitte Technology Fast 500™ for four years, was named a leader in IDC MarketScape: Worldwide Influencer Marketing Platforms for Large Enterprises in 2025, was named a Leader by The Forrester New Wave™: Influencer Marketing Solutions, and has been consistently recognized by G2 as a Leader, and is rated 5 stars on Influencer MarketingHub. We operate in a flexible work model that combines both in-person and remote work to boost collaboration, enhance innovation, and adapt to individual work styles.

We're seeking passionate, innovative minds to join our journey. Be a part of our dynamic team and let's transform the industry together!

MLOPS / DEVOPS ENGINEER – AI INFRASTRUCTURE

The DevOps Engineer is responsible for supporting and improving cloud and ML/AI infrastructure, automating deployments, and maintaining CI/CD pipelines to ensure efficient, secure, and scalable development workflows. This role plays a crucial part in infrastructure automation, monitoring, and cloud security while collaborating with Software and ML Engineers, Product support, QA, and Security teams.As a key member of the DevOps team, the DevOps Engineer helps manage cloud environments, CI/CD pipelines, and Infrastructure as Code (IaC), ensuring high availability and compliance with security best practices.

IN THIS ROLE, YOU’LL GET TO:

CLOUD INFRASTRUCTURE, SECURITY & RELIABILITY

• Support and maintain scalable, highly available, and secure cloud infrastructure in accordance with company policies and standards.
• Provision and manage cloud resources using Infrastructure as Code (Terraform, Terragrunt, CloudFormation).
• Implement cloud security best practices, including IAM/role-based access controls, encryption, vulnerability management, and secure infrastructure configurations.
• Support containerized environments and orchestration platforms.
• Apply DevSecOps principles across infrastructure and deployment workflows.
• Participate in disaster recovery planning, testing, and recovery activities.

CI/CD, AUTOMATION & DEPLOYMENT

• Maintain and optimize CI/CD pipelines using tools such as GitLab CI/CD and Jenkins, supporting application and ML model deployments.
• Improve deployment reliability and support zero-downtime deployment strategies.
• Automate configuration management, infrastructure provisioning, and routine operational processes.
• Troubleshoot deployment and pipeline issues and implement improvements to prevent recurrence.
• Develop scripts and automation to reduce manual work and improve engineering efficiency.

AI & AGENTIC INFRASTRUCTURE

• Help design, deploy, operate, and secure infrastructure supporting AI and agentic products, including MCP, agents, integrations, internal tooling, and customer-facing use cases.
• Use AI-assisted engineering tools, coding copilots, and AI-driven troubleshooting to improve DevOps productivity and reduce repetitive operational work.
• Evaluate and adopt practical AI-enabled workflows that improve infrastructure management, troubleshooting, and operational efficiency.

MLOPS & ML PLATFORM INFRASTRUCTURE

• Operate and scale ML platform infrastructure, including Databricks and Sagemaker clusters, jobs compute, ML pipelines, and Model Serving endpoints.
• Manage production model-serving infrastructure, including compute capacity, provisioned throughput, and autoscaling for high-throughput inference workloads.
• Maintain infrastructure-level monitoring for model drift, data quality, inference performance, and serving health, while partnering with ML Engineering on model evaluation, quality thresholds, and model correctness.
• Partner with ML Engineering to support reliable CI/CD and production deployment of ML models.

OBSERVABILITY, INCIDENT RESPONSE & ENGINEERING COLLABORATION

• Maintain monitoring, logging, metrics, and alerting solutions using tools such as Prometheus, Grafana, Coralogix, and CloudWatch.
• Support incident response and perform Root Cause Analysis (RCA) for infrastructure and deployment-related issues.
• Improve system observability through effective log aggregation, metrics collection, monitoring, and alerting.
• Partner with Software Engineers, ML Engineers, QA, and Software Engineers in Test to improve deployment workflows and integrate automated testing into CI/CD pipelines.
• Collaborate with IT Security to maintain secure cloud operations and infrastructure policies.
• Respond to engineering and Product Support requests in a timely manner and provide technical infrastructure support when needed.
• Maintain accurate internal technical and operational documentation.
• Collaborate effectively with international teams across multiple time zones

WHO YOU ARE AND WHAT YOU’LL NEED FOR THIS POSITION:

• 3+ years of experience in DevOps, Cloud Engineering, Site Reliability Engineering (SRE), or a similar infrastructure-focused role.
• 2+ years of hands-on experience supporting production ML/AI infrastructure, including model serving, training pipelines, and model monitoring.
• 2+ Hands-on experience with Databricks (clusters, jobs, ML pipelines, Model Serving) and/or AWS SageMaker (endpoints, inference, model deployment, provisioned throughput, autoscaling) in a production environment.
• 2+ years of hands-on experience with AWS services such as EC2, S3, RDS, Lambda, IAM, VPC, SQS, API Gateway, or similar services.
• 2+ years of experience working with containerized environments and orchestration platforms such as Kubernetes and Amazon EKS.
• Strong experience building and maintaining CI/CD pipelines using tools such as GitLab CI/CD or Jenkins.
• Hands-on experience with Infrastructure as Code using Terraform, Terragrunt, CloudFormation, or similar technologies.
• Strong Linux system administration and troubleshooting skills.
• Solid understanding of networking fundamentals, including routing, load balancing, network security, and related concepts.
• Scripting experience with Python, Bash, or similar languages to automate infrastructure and operational tasks.

NICE TO HAVE

• Experience with Google Cloud, particularly for candidates who have worked across multi-cloud environments.
• Familiarity with Helm and service mesh technologies such as Istio, Linkerd, Traefik, or similar tools.
• Experience designing serverless and event-driven architectures (beyond basic usage) using AWS Lambda, API Gateway, and SQS.
• Exposure to cloud and infrastructure security practices, including vulnerability management and tools such as Nessus, Prowler, Trivy, or firewalls.
• Knowledge of security standards, compliance requirements, and cloud security best practices.
• Experience with observability, log analysis, and monitoring platforms such as Coralogix, Prometheus, Grafana, or similar solutions.
• FinOps experience, including cloud cost monitoring, optimization, and accountability practices.
• Experience with API gateway or API management platforms such as Kong or Apigee.
• Hands-on experience using AI tools to improve engineering workflows, automation, troubleshooting, or agentic use cases.

Confidence can sometimes hold us back from applying for a job. But we'll let you in on a secret: there's no such thing as a 'perfect' candidate. Have 50% of the criteria? Excited about this opportunity? Passionate about what we do at CreatorIQ? CreatorIQ is a place where everyone can grow.

WHAT YOU WILL GET FROM US:

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