Platform Engineer, Cloud Infrastructure

Salesforce

Confirmed live yesterday High trust
Remote

Quick summary

Work type
Remote
Location
Redwood City, CA
Salary
$148,500–$223,900 / yr
Posted
74 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $179k
This role $186k
$103k most similar roles pay here $237k

This role pays more than 65% of similar roles. Most pay $151,000–$207,914 — the shaded band above. At the midpoint, this role pays about $186k versus about $179k 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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At a glance

TL;DR · Platform Engineer, Cloud Infrastructure

Platform Engineer — Cloud Infrastructure (SMTS) is a member of the Platform Engineering team within the Cloud Infrastructure organization. This role focuses on building next-generation, self-healing platform tools by integrating AI, LLMs, and autonomous agents into multi-cloud services to improve reliability and developer experience. You will develop core platform services using Go and Python, design multi-agent workflows for complex operational tasks, and build Retrieval-Augmented Generation systems over internal documentation. Key responsibilities include creating AIOps systems for anomaly detection, developing custom CLI plugins, and maintaining GitOps pipelines using Flux, Argo CD, Pulumi, and Terraform. The role addresses the challenge of reducing operational toil across Kubernetes clusters on AWS, Azure, GCP, and OCI. You will leverage your expertise in vector databases, prompt engineering, and cloud-native infrastructure to automate production systems and mentor others on AI-driven platform concepts.

What does a Platform Engineer earn?

Median $150000 from 32 postings across 22 companies.

See salary data

What you'll do

  • Develop core platform services and infrastructure automation using Go and Python.
  • Build AIOps systems using LLMs and autonomous agents to automate root-cause analysis and self-healing remediation.
  • Create Retrieval-Augmented Generation (RAG) applications over internal documentation and incident data to reduce mean time to resolution.
  • Develop custom tools, CLI plugins, and Model Context Protocol integrations to connect cloud infrastructure APIs to agentic coding tools.
  • Maintain continuous deployment pipelines using GitOps tooling and infrastructure-as-code frameworks like Flux, Argo CD, Pulumi, or Terraform.
  • Identify repetitive operational tasks and build agentic solutions to automate manual work for SRE and platform teams.
  • Mentor engineers on AI/ML concepts, prompt engineering, and agentic design patterns.
  • Participate in on-call rotations and apply an AI-first perspective to incident management and post-mortems.

What we're looking for

  • Must have 5+ years of professional experience in software engineering, platform engineering, or DevOps with a focus on AI solutions.
  • Must possess strong knowledge of core AI/ML concepts including LLM optimization, embedding models, vector databases, and prompt engineering.
  • Must have experience building with agentic frameworks and LLM orchestration tooling for multi-step autonomous tasks.
  • Must have proficient programming skills in Golang and Python to build production-grade backend services and APIs.
  • Must have hands-on experience with Kubernetes and multi-cloud environments including AWS, Azure, GCP, or OCI.
  • Must be familiar with GitOps tools like Flux or Argo CD and infrastructure-as-code frameworks like Pulumi or Terraform.
  • Must demonstrate an agentic mindset with a proven track record of using AI to automate complex workflows and handle non-deterministic outputs.
  • Must possess strong communication skills to mentor others on AI/ML concepts and advocate for AI solutions across engineering teams.

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