DevOps Engineer, GovCloud Mid/Senior

Salesforce

Confirmed live 2 days ago High trust
Remote

Quick summary

Work type
Remote
Location
Remote
Salary
$96,300–$260,100 / yr
Posted
44 days ago
Freshness
Confirmed live 2 days ago
Closes
Oct 26, 2026

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $156k
This role $178k
$77k most similar roles pay here $280k

This role pays more than 71% of similar roles. Most pay $126,750–$185,875 — the shaded band above. At the midpoint, this role pays about $178k versus about $156k for comparable roles.

Based on 240 similar postings.

Employer

About Salesforce

Salesforce is the world''s leading customer relationship management (CRM) platform, offering cloud-based software for sales, service, marketing, analytics, and application development. Industry: Enterprise Software & Cloud Computing

Salesforce currently has 106 open roles on FindRole.

Listed pay typically runs $148,500–$260,100 across 98 roles with salary data.

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View all roles at Salesforce

At a glance

TL;DR · DevOps Engineer, GovCloud Mid/Senior

The DevOps Engineer, GovCloud Mid/Senior joins a team of Systems, Site Reliability, and DevOps Engineers focused on ensuring maximum availability, performance, and security compliance for Government Cloud infrastructure. This role involves solving infrastructure problems with reusable code, building compute capacity, managing Kubernetes deployments at scale, and developing automated CI/CD pipelines. The candidate will design complex systems where AI agents integrate into human workflows while maintaining shared system context to ensure reliable outputs. Key technical requirements include expertise in AWS environments, IaaS-based TCP/IP networking (Transit Gateway, VPC, Security Groups), Docker, and Kubernetes. Proficiency is required in Terraform, Ansible, Linux systems engineering, and scripting languages like Shell, Python, or Golang. Additionally, the role demands advanced prompt engineering skills and experience with tools such as Spinnaker, Jenkins, Splunk, and ELK to manage highly sensitive customer data environments.

What does a DevOps Engineer earn?

Median $126800 from 89 postings across 26 companies.

See salary data

What you'll do

  • Manage and optimize Government Cloud infrastructure to ensure maximum availability and security compliance.
  • Build and maintain scalable Kubernetes deployments and manage infrastructure using Terraform or Ansible.
  • Develop, automate, and iterate on CI/CD pipelines to increase feature velocity for internal teams.
  • Perform advanced prompt engineering to create reliable, secure, and production-ready AI outputs.
  • Design and orchestrate complex systems where AI agents integrate into human workflows at scale.
  • Maintain a shared system context repository of designs and constraints to ensure accurate AI operations.
  • Evaluate both human and AI-generated code for correctness, security, and performance.
  • Transform manual, human-heavy processes into automated governance solutions using infrastructure as code.

What we're looking for

  • Must be a U.S. Citizen capable of passing Criminal Justice Information Services screening and fingerprint scans.
  • Proven expertise in AWS environments, including infrastructure build and optimization.
  • Skilled in IaaS based TCP/IP networking protocols such as transit gateway, VPC, security groups, and Route tables.
  • 3+ years experience deploying distributed applications with Docker and Kubernetes (EKS, GKE).
  • 3+ years of experience in Infrastructure as Code and configuration management using Terraform or Ansible.
  • 3+ years of Linux system engineering experience.
  • 2+ years of experience managing infrastructure/application security for highly sensitive data (IAM, CI/CD, PKI).
  • 3+ years of experience with CI orchestration services like Spinnaker or Jenkins.
  • 2+ years of experience with scripting and programming languages such as Shell, Python, or Golang.
  • Advanced prompt engineering skills to create reliable, secure, and production-ready AI outputs.
  • Demonstrated AI-first approach using tools like GitHub Copilot or Claude Code in development workflows.

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