Mid-Level Site Reliability Engineer — Remote AI/ML Cloud

SMX; Jackson (MS); Remote; USD 96,000 - 161,000; Full time

Benefits offered by this job

Health insurance

Paid leave

Retirement plan

Job summary

SMX seeks a Mid-Level Site Reliability Engineer to architect, automate, and operate cloud infrastructure for AI/ML platforms. You will bridge MLOps and DevSecOps, deploying scalable architectures across commercial, private, hybrid, and government clouds.

Beyond platform engineering, you will be a customer-facing SME, translating mission challenges into architectures, demonstrating platform capabilities, and supporting technical scoping during engagements.

Qualifications

• 3–5 years in Site Reliability Engineering, DevOps or Platform Engineering.
• Ability to communicate complex infra concepts to stakeholders as a technical SME.
• Strong Kubernetes and container networking, RBAC, Pod Security, secrets management.
• Cloud IaC across AWS, Azure, GCP; Terraform or equivalent tooling; Git workflows.
• Automation proficiency in Python, Bash, or Go.
• Familiarity with CIS/NIST/FedRAMP security baselines.

Responsibilities

• Architect, deploy, and maintain highly available Kubernetes clusters for AI/ML workloads.
• Serve as technical SME on client engagements; present solutions and scope during engagements.
• Collaborate with delivery and account teams to scope and validate modern AI/ML and DevSecOps architectures.
• Drive infrastructure automation using Terraform and GitOps with security controls from day one.
• Build and sustain CI/CD pipelines with container vulnerability scans, artifact tracking, and audit logs.
• Monitor platform performance and participate in on-call rotations; perform RCAs and post-mortems.

Skills

Kubernetes

Cloud platforms

IaC (Terraform)

Python/Bash/Go

Security fundamentals

Client engagement

Tools

Terraform

GitOps

Prometheus

Grafana

Datadog

Splunk

Job description

SMX seeks a Mid-Level Site Reliability Engineer to architect, automate, and operate cloud infrastructure for AI/ML platforms. You will bridge MLOps and DevSecOps, deploying scalable architectures across commercial, private, hybrid, and government clouds.

Beyond platform engineering, you will be a customer-facing SME, translating mission challenges into architectures, demonstrating platform capabilities, and supporting technical scoping during engagements.