Senior Cloud Platform Engineer (SMTS)

As a Senior Member of Technical Staff (SMTS) within our Monitoring Cloud team, you will be a key owner and operator of the systems that keep Salesforce reliable. You won’t just be “using” tools; you will be productizing infrastructure to ensure our monitoring capabilities evolve at the scale of our multi-cloud footprint. Your mission is to bridge the gap between high-level feature design and deep-system stability. From automating the “paved path” across AWS and GCP to securing air-gap environments for our most sensitive customers, you will ensure our monitoring stack is invisible, resilient, and intelligent. This is an AI-first engineering role. You will use AI-assisted development tools (e.g., Claude Code) as the default for every inner-loop activity, code authoring, Terraform and Kubernetes scaffolding, test generation, refactoring, log/trace analysis, runbook drafting, and documentation. We expect AI to compound your throughput on routine implementation so you can focus your human judgment on architecture, security, on-call response, and customer outcomes.

Core Responsibilities

1. Infrastructure as Code (IaC) & Automation Design and implement automation frameworks using Terraform and Kubernetes to manage monitoring infrastructure. Standardize “paved path” deployments across AWS and GCP, eliminating manual configuration errors and ensuring global consistency. Use AI-assisted tooling as the default for authoring, refactoring, and reviewing IaC modules, Helm charts, and automation scripts while directing intent, validating output, and owning the final result.

2. Infrastructure Upkeep & Productization Own the lifecycle of the Monitoring Cloud stack, including version upgrades and performance tuning. Productize core components (e.g., Grafana, custom Terraform providers) to make them consumable as reliable services by internal engineering teams. Leverage AI for upgrade planning, release-note analysis, migration scaffolding, and boilerplate-heavy productization work (API wiring, schema plumbing, SDK generation), while retaining accountability for design and rollout.

3. Secure & Air-Gapped Operations Deploy and manage the full monitoring stack within highly isolated, air-gapped environments. Ensure that our most secure customer segments receive the same level of observability and reliability as our public cloud offerings. Apply AI assistance during development of the artifacts that ship into these environments; operate them in-network with the disciplined, human-driven workflows these environments require.

4. Operational Excellence & Health Participate in the team’s on-call rotation, providing the deep technical expertise required to maintain strict SLAs and availability targets. Conduct root-cause analysis (RCA) for complex system failures and implement long-term preventative fixes. Address support requests with a “customer first” mindset Use AI as a co-pilot during incident response and RCA: summarizing logs, correlating traces, proposing hypotheses, and drafting status updates and postmortem while the engineer remains the accountable responder and decision-maker.

5. Next-Gen Feature Delivery Design and deliver platform features that adhere to enterprise standards while pioneering AI-driven development practices to accelerate delivery and enhance system intelligence. Contribute to and evolve the team’s AI-assisted development playbook: prompts, agents, skills, evaluation harnesses, and guardrails that let the team ship faster without sacrificing quality or security.

5+ years Proven track record in Distributed systems, API platforms, Infrastructure Engineering, Observability or DevOps at scale. Proficiency with Kubernetes (K8s) and Terraform. Hands-on experience managing infrastructure in AWS and/or GCP. Proficiency in programming languages(eg: java, python etc) Experience managing or extending monitoring tools (e.g., Grafana), messaging systems (kafka etc), elastic search, caching frameworks Security First: Understanding of authN/authZ security protocols, particularly in managing isolated or restricted network environments. AI-assisted development fluency: demonstrated use of AI coding assistants (e.g., Claude Code) as part of a daily engineering workflow, able to prompt effectively, critically evaluate generated code, and integrate AI into IaC, testing, and automation pipelines.

benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.

In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. Salesforce offers a variety of benefits to help you live well including: time off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock purchasing program. More details about company benefits can be found at the following link: https://www.salesforcebenefits.com.Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records.

At Salesforce, we believe in equitable compensation practices that reflect the dynamic nature of labor markets across various regions. The typical base salary range for this position is $148,500 - $223,900 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $178,900 - $246,000 annually. The range represents base salary only, and does not include company bonus, incentive for sales roles, equity or benefits, as applicable.

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