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DevOps Engineer

Remote / Online - Candidates ideally in
New York, New York County, New York, 10261, USA
Listing for: Socket.dev
Full Time, Remote/Work from Home position
Listed on 2026-09-07
Job specializations:
  • IT/Tech
    Cloud Computing: Infrastructure & Operations, SRE/Site Reliability
Salary/Wage Range or Industry Benchmark: 120000 - 180000 USD Yearly USD 120000.00 180000.00 YEAR
Job Description & How to Apply Below
Location: New York

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 Built In 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 Market Scape:
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 Marketing Hub. 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!

Dev Ops Engineer

The Dev Ops 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 Dev Ops team, the Dev Ops 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, Cloud Formation).
  • 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 Dev Sec Ops  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 Git Lab 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 Dev Ops 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…
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