Cloud Infrastructure Engineer

Salesforce

Member of Technical Staff building and operating core platform services across AWS, Azure, GCP, and OCI. Contributing to Kubernetes automation and AI-augmented engineering workflows at Salesforce.

Posted 7/30/2026full-timeRedwood City • California • 🇺🇸 United StatesJuniorMid-Level💰 $117,200 - $176,700 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in cloud infrastructure engineering, particularly with Kubernetes and multi-cloud environments, while leveraging AI tools to enhance productivity and streamline operations. Proficient in programming with Go and Python, contributing to automation and continuous deployment practices.

Highest-signal resume keywords

Kubernetes ExperienceGolang ProgrammingPython ProgrammingGitOps (Flux, Argo CD)Infrastructure-as-Code (Pulumi, Terraform)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

KubernetesGolangPythonGitOpsFluxArgo CDPulumiTerraformCloud Infrastructure EngineeringContinuous Deployment

Soft Skills

Strong CommunicationCollaborationEagerness to Learn

Tools & Technologies

AWSAzureGCPOCIAI Tools

Industry Keywords

Multi-CloudAutomationOperational PostureObservabilityAgentic Mindset

Tech Stack

Tools & technologies

AWSAzureCloudFluxGoGoogle Cloud PlatformKubernetesPythonTerraform

About the role

Key responsibilities & impact

Success will be measured by your growing contributions to the reliability, scalability, and developer experience of the platform services our team builds and operates across our multi-cloud Kubernetes fleet.
Build and maintain platform services and automation in Go and Python that help manage Kubernetes clusters across AWS, Azure, GCP, and OCI.
Contribute to continuous deployment pipelines using GitOps tooling (Flux, Argo CD) and infrastructure-as-code frameworks (Pulumi, Terraform) to enable safe, repeatable releases.
Take part in fleet initiatives such as cluster lifecycle automation, upgrades, policy enforcement, and observability improvements, with guidance from senior engineers.
Partner with SRE, security, and product engineering teams to understand their needs and help deliver self-service platform capabilities that reduce toil.
Be an AI amplifier : use AI tooling in your everyday engineering workflows — agentic coding assistants (e.g., Claude Code) for development, code review, automation, and operational runbooks — to force-multiply your output as you ramp.
Develop an agentic mindset : learn to spot repetitive operational work and propose agent-driven or AI-augmented automations that reduce manual effort.
Participate in design reviews and code reviews, write clear technical documentation, and grow your platform and cloud-native expertise.
Join on-call rotations as you ramp and help improve the operational posture of the platform through automation and post-incident learning.

Requirements

What you’ll need

2 - 4 years of professional experience in cloud infrastructure engineering and continuous deployment.
Hands-on Kubernetes experience — deploying, troubleshooting, and automating workloads or clusters (networking, scaling, upgrades).
Good programming skills in Golang and/or Python, with experience building services, CLIs, or automation tooling.
Multi-cloud exposure, primarily AWS, with a working understanding of core compute, networking, IAM, and managed Kubernetes services.
Familiarity with GitOps using Flux or Argo CD, and infrastructure-as-code with Pulumi (or comparable tooling such as Terraform).
Demonstrated AI literacy and an emerging agentic mindset — you actively use AI tools in your daily engineering work (code generation, debugging, documentation, automation) and can speak to how AI has amplified your output.
Strong communication and collaboration skills, and an eagerness to learn and grow within a fast-moving platform team.

Benefits

Comp & perks

time off programs
medical, dental, vision
mental health support
paid parental leave
life and disability insurance
401(k)
employee stock purchasing program