Platform Engineer — Cloud Infrastructure; SMTS
Job in
Redwood City, San Mateo County, California, 94061, USA
Listed on 2026-07-03
Listing for:
Salesforce, Inc.
Full Time
position Listed on 2026-07-03
Job specializations:
-
Software Development
AI Engineer (Applied/Software), Cloud Engineer - Software, DevOps
Job Description & How to Apply Below
Skip to main content#Platform Engineer — Cloud Infrastructure (SMTS) page is loaded## Platform Engineer — Cloud Infrastructure (SMTS)
Apply remote type:
Office
- Flexible locations:
California
- Redwood Citytime type:
Full time posted on:
Posted Todayjob requisition :
JR347709
* To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.
* Job Category Software Engineering Job Details
**** About Salesforce
**** Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.
Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce.
Platform Engineering — Cloud Infrastructure Overview of the Role The SMTS role is part of our Platform Engineering team within the Cloud Infrastructure organization. Platform Engineering is made up of platform engineers, SREs, and Dev Ops specialists who design, build, and operate the internal developer platform powering hundreds of Kubernetes clusters across AWS, Azure, GCP, and OCI. Whether we are automating cluster lifecycle management, hardening our Git Ops delivery pipelines, or architecting autonomous agents to manage production systems, we strive to give every product team a fast, secure, and reliable path to production.
We are looking for a Senior Member of Technical Staff with strong AI/ML software engineering expertise to build the next generation of intelligent, self-healing platform tools. Instead of managing GPU hardware, your focus will be applying AI solutions directly to infrastructure and operations problems. You will write core platform services in Go and Python, design multi-agent workflows to automate complex operational tasks, build RAG systems over engineering documentation, and act as the core AI amplifier — architecting the intelligent systems that multiply the entire engineering organization's output.
What You’ll Actually Be Doing Success will be measured by how effectively you integrate AI, LLMs, and autonomous agents into our multi-cloud platform services to improve system reliability, reduce operational toil, and elevate the developer experience.
Design, build, and operate platform services and infrastructure automation in Go and Python, embedding AI capabilities directly into the core platform software.
Architect and implement intelligent, closed-loop automation systems (AIOps) that leverage LLMs and autonomous agents to detect anomalies, perform root-cause analysis, and execute self-healing remediation playbooks.
Build and maintain Retrieval-Augmented Generation (RAG) applications over internal platform documentation, runbooks, and historical incident data to drastically reduce engineering MTTR.Develop custom tools, CLI plugins, and Model Context Protocol (MCP) integrations that connect our cloud infrastructure APIs to agentic coding tools (like Claude Code), turning standard automation into autonomous workflows.
Partner with SRE, security, and platform specialists to identify highly repetitive operational work and build agentic solutions that delegate that toil to AI.Maintain and improve standard continuous deployment pipelines using Git Ops tooling (Flux, Argo CD) and infrastructure-as-code frameworks (Pulumi, Terraform) to ensure safe, repeatable delivery of both traditional platform code and AI-driven solutions.
Participate in design reviews, write clear technical documentation and RFCs, and mentor traditional platform engineers on AI/ML concepts, prompt engineering, and agentic design patterns.
Contribute to on-call rotations and continuously bring an AI-first perspective to improving incident management and platform post-mortems.
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