Site Reliability Engineer (5757)

smxtech; United States; Remote; USD 90,000 - 130,000; Full time

Job summary

smxtech is seeking a mid-level site reliability engineer to design, automate, and operate cloud platforms that support AI/ML workloads. The role blends hands-on infrastructure engineering with customer-facing technical consultation across commercial, private, hybrid, and government cloud environments.

You will build and maintain Kubernetes clusters, automate with IaC (Terraform), implement security baselines, develop CI/CD pipelines, and monitor platform health.

Qualifications

• 3-5 years in site reliability, DevOps, or platform engineering.
• Strong Kubernetes operations including networking, RBAC, pod security, and secrets management.
• Practical experience managing infrastructure on a major cloud platform, including networking, identity, encryption, security, and logging.
• Experience with Terraform or equivalent infrastructure-as-code tools and Git workflows.
• Proficiency in Python, Bash, or Go for automation and tooling.
• Ability to explain infrastructure clearly to customers and troubleshoot across layers; awareness of CIS/NIST baselines.

Responsibilities

• Build and maintain highly available Kubernetes clusters for AI/ML training, inference, and GPU use.
• Consult with customer stakeholders to understand requirements, explain technical options, and support demonstrations.
• Partner with delivery and account teams to validate architectures for AI/ML platforms and secure software delivery.
• Automate infrastructure with Terraform or comparable tools and Git-based workflows, incorporating security controls.
• Create resilient CI/CD pipelines with container vulnerability scanning, artifact tracking, and audit logs.
• Monitor capacity and platform health, participate in on-call support, and document operational lessons.
• Produce technical diagrams, reference architectures, runbooks, and client handoff materials.

Skills

Kubernetes ops

Cloud infra management

Terraform

Git workflows

Python/Bash/Go

Tools

Prometheus

Grafana

Splunk

Datadog

Job description

Role overview

Design, automate, and operate cloud platforms that support compute-intensive AI and machine learning workloads. This mid-level site reliability role combines hands-on infrastructure engineering with customer-facing technical consultation across commercial, private, hybrid, and government cloud environments.

Responsibilities

• Build and maintain highly available Kubernetes clusters for AI and ML training, inference, and GPU use.
• Consult with customer stakeholders to understand requirements, explain technical options, and support solution demonstrations and scoping.
• Partner with delivery and account teams to validate architectures for AI/ML platforms and secure software delivery.
• Automate infrastructure with Terraform or comparable tools and Git-based workflows, incorporating security controls and compliance safeguards.
• Create resilient CI/CD pipelines with container vulnerability scanning, artifact tracking, and audit logs.
• Monitor capacity and platform health, participate in on-call support, investigate root causes, and document operational lessons.
• Produce technical diagrams, reference architectures, runbooks, and client handoff materials.

Requirements

• 3-5 years of experience in site reliability, DevOps, or platform engineering.
• Strong Kubernetes operations skills, including networking, role-based access control, pod security, and secrets management.
• Practical experience managing infrastructure on a major cloud platform, including networking, identity, encryption, security, and logging.
• Experience with Terraform or equivalent infrastructure-as-code tools and Git workflows.
• Proficiency in Python, Bash, or Go for automation and tooling.
• Ability to explain infrastructure clearly to customers, troubleshoot across compute, storage, networking, and application layers, and apply security baselines such as CIS or NIST concepts.

Nice to have

• Experience operating infrastructure for AI/ML workloads or in government and regulated cloud environments.
• Familiarity with hybrid, multi-cloud, or private cloud architectures and observability tools such as Prometheus, Grafana, Splunk, or Datadog.
• Relevant cloud or cloud-native certifications.

Benefits and work setup

• Fully remote position open to candidates in the United States.
• Benefits include health insurance, paid leave, retirement, and learning and development opportunities.