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.