DevOps & AI/ML Infrastructure Engineer

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!

DEVOPS & AI/ML INFRASTRUCTURE ENGINEER

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 interactive 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 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.

• Hands-on experience using AI tools to improve engineering workflows, automation, troubleshooting, or agentic use cases.

• Experience supporting data, ML, or other compute-intensive production workloads.

• Experience with Google Cloud would be valuable, 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 would be beneficial.

• Experience with serverless and event-driven architectures using technologies such as AWS Lambda, API Gateway, and SQS is a plus.

• Exposure to cloud and infrastructure security practices, including vulnerability management and tools such as Nessus, Prowler, Trivy, firewalls, or similar technologies, would be valuable.

• Knowledge of security standards, compliance requirements, and cloud security best practices is beneficial.

• Experience with observability, log analysis, and monitoring platforms such as Coralogix, Prometheus, Grafana, or similar solutions is a plus.

• FinOps experience, including cloud cost monitoring, optimization, and accountability practices, would be valuable.

• Experience with API gateways or API management platforms such as Kong, Apigee, or similar technologies is beneficial.

• Experience with MLOps platforms and practices—particularly Databricks, model serving, ML pipelines, and model monitoring—would be an advantage.

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? Please apply! CreatorIQ is a place where everyone can grow.

What you will get from us:

• People: Work with talented, collaborative, and friendly peopl