Software Engineering PMTS

Salesforce•San Francisco, CA

3d•$197,300 - $344,700•Hybrid

About The Position

As a Software Engineer on the Cloud Infrastructure Automation team at Salesforce, you are part of a team that delivers automation tools, frameworks, workflows, and validation platforms across public cloud platforms including AWS, GCP, Azure, and Alibaba. You build and operate resilient distributed systems running across thousands of compute nodes in multiple data centers, contributing to open source technology and driving innovations that improve system availability, resilience, and performance. You bring an AI-first mindset to your engineering practice, using AI tools to move faster, build fluency across the stack, and contribute well beyond your core specialty.

Requirements

10+ years of backend software development experience with deep knowledge of programming in Java, Go, Python, or Ruby, and experience owning and operating multiple instances of critical services.
A demonstrated AI-first approach to engineering, including hands-on experience with AI development tools (e.g., GitHub Copilot, Cursor, Claude, OpenAI API) and advanced prompt engineering skills to produce reliable, secure, production-ready outputs.
Experience with critical infrastructure services including monitoring, alerting, logging, and reporting applications, as well as agile development and Test-Driven Development (TDD) methodologies.
Experience contributing to and maintaining shared system context — explicit repositories of system designs, constraints, and standards that enable AI to operate accurately and reliably.

Nice To Haves

Experience with distributed database systems and relational databases such as PostgreSQL.
Familiarity with open source technologies such as Spinnaker or Zookeeper.
Experience writing microservices on containerization frameworks such as Mesos

Responsibilities

Design, develop, and operate resilient distributed systems and cloud infrastructure automation tools across public cloud platforms (AWS, GCP, Azure, Alibaba), using Infrastructure-as-Code practices with Terraform and containerization frameworks such as Kubernetes and Docker.
Build and ship high-quality, production-grade software using modern engineering practices, with AI as a core part of your development workflow — pushing the boundaries of AI development tools to deliver secure, optimized, and high-quality code.
Design and orchestrate complex systems where AI agents integrate seamlessly into human workflows, and critically evaluate both human- and AI-generated code for correctness, quality, security, and performance.
Participate in the team's on-call rotation to address complex problems in real time, balancing live-site management, feature delivery, and retirement of technical debt.