Platform Engineer - Cloud Infrastructure (SMTS)

salesforce.com, inc.; Redwood City (CA); On-site; USD 148,500 - 223,900; Full time

Benefits offered by this job

Medical, dental, and vision insurance

401(k)

Employee stock purchasing program

Job summary

Salesforce.com, inc. is seeking a Senior Member of Technical Staff in Redwood City to drive AI/ML integration in platform services. Candidates should have extensive experience in software engineering with a focus on automation and operational efficiency. Flexibility to work on diverse platforms and architectures is essential.

This role offers a competitive compensation package, including comprehensive employee benefits and stock purchasing options, aiming to attract driven professionals looking to shape the future of cloud infrastructure.

Qualifications

• 5+ years in software engineering, DevOps, focusing on AI solutions.
• Understanding of core AI and ML concepts applied to software.
• Programming skills in Golang and Python.

Responsibilities

• Design and operate platform services with AI integration.
• Implement intelligent automation systems leveraging LLMs.
• Mentor engineers on AI/ML concepts and agentic design.

Skills

AI/ML software engineering

Golang

Python

Kubernetes

Cloud-native infrastructure

Tools

GitOps

Terraform

Pulumi

Job description

Role Overview

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 DevOps 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 GitOps 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.

Responsibilities

• 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 GitOps 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.

Qualifications

• 5+ years of professional experience in software engineering, platform engineering, or DevOps, with a recent, heavy focus on building and implementing AI solutions.
• Strong understanding of core AI and ML concepts applied practically to software engineering, including LLM context window optimization, embedding models, semantic search, vector databases, and prompt engineering/tuning.
• Experience building with agentic frameworks and LLM orchestration tooling to execute multi‑step, autonomous tasks.
• Good programming skills in Golang and Python, with the ability to build production‑grade backend services, APIs, and microservices.
• Solid fundamental knowledge of cloud‑native infrastructure, with hands‑on experience in Kubernetes and multi‑cloud environments (AWS, Azure, GCP, or OCI).
• Familiarity with continuous deployment and infrastructure‑as‑code concepts (GitOps with Flux/Argo CD, Pulumi, or Terraform).
• Demonstrated agentic and automation mindset—proven track record of using AI to automate complex workflows and deep understanding of designing AI systems to handle edge cases, tool‑calling errors, and non‑deterministic outputs.
• Strong communication and collaboration skills, with a passion for teaching, raising the team’s AI literacy, and evangelizing AI solutions across engineering boundaries.

Preferred Qualifications

• Hands‑on experience building custom extensions, plugins, or Model Context Protocol (MCP) servers for agentic developer tools like Claude Code or GitHub Copilot.
• Experience applying AI specifically to observability data (parsing logs, analyzing metrics, or correlating distributed traces) for predictive scaling or automated alerting.
• Deep experience working with vector databases (e.g., Pinecone, Qdrant, Milvus, pgvector) inside platform applications.
• Experience operating AI‑driven tools within compliance‑driven environments (FedRAMP, SOC 2), ensuring strong data privacy boundaries, LLM guardrails, and secure handling of sensitive cloud credentials.
• Experience with internal developer platforms (IDPs), platform APIs, or building developer experience (DevEx) tooling.
• Contributions to open‑source projects is a plus.

Benefits

We offer a competitive benefits package that includes time off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock purchasing program. Additional details can be found at our benefits website.

Compensation

Base salary range for this position is $148,500 – $223,900 annually in the United States; in selected cities within the San Francisco and New York City metropolitan areas the range is $178,900 – $246,000 annually. The stated amount is base salary only, excluding any company bonus, incentive compensation, equity, or benefits.

Accommodations

If you need a reasonable accommodation during the application or recruiting process, please submit a request via the accommodations form.

EEO Statement

Salesforce is an equal‑opportunity employer and maintains a policy of non‑discrimination with all employees and applicants for employment. Candidates will be assessed on merit, competence, and qualifications without regard to race, religion, color, national origin, sex, sexual orientation, gender identity, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint or other classifications protected by law. This policy applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination and all related matters.