Senior Cloud Platform Engineer (SMTS)

Engg; Bellevue, Washington (WA, Washington County); Hybrid; USD 180,000 - 240,000; Full time

Job summary

Salesforce is seeking a Senior Software Engineer to join Infrastructure Engineering / Monitoring Cloud across Bellevue/Seattle/SF/Palo Alto. You will design and implement automation, manage IaC with Terraform and Kubernetes, and drive AI-assisted improvements for monitoring stacks.

You will own lifecycle upgrades, productize components like Grafana and Terraform providers, and operate in air-gapped environments while maintaining strict on-call practices and security standards in a high-scale

Qualifications

• 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 (e.g., Java, Python).
• Experience managing or extending monitoring tools (Grafana), messaging systems (Kafka), Elasticsearch, caching frameworks.
• Security-first: understanding of authN/authZ security protocols in isolated or restricted networks.
• AI-assisted development fluency: demonstrated use of AI coding assistants (e.g., Claude Code) as part of a daily engineering workflow.

Responsibilities

• 1. Design and implement automation frameworks using Terraform and Kubernetes to manage monitoring infrastructure.
• 2. Standardize deployments across AWS and GCP with AI-assisted tooling.
• 3. Own the lifecycle of the Monitoring Cloud stack, including upgrades and performance tuning.
• 4. Productize core components (Grafana, Terraform providers) as reliable services for internal teams.
• 5. Deploy and operate the monitoring stack in air-gapped environments.
• 6. Participate in on-call rotations and perform RCA with a customer-first mindset, using AI to assist in incident response.
• 7. Design and deliver AI-driven platform features and contribute to the AI development playbook.

Skills

Distributed systems

API platforms

Infrastructure Engineering

Observability

DevOps

Kubernetes

AI-assisted development

Security

Java

Python

Grafana

Kafka

Elasticsearch

Tools

Terraform

Kubernetes

Grafana

AWS

GCP

Job description

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.

Location: Bellevue / Seattle / San Francisco / Palo Alto/ Hybrid / On-Site

Role Level: Software Engineering Senior MTS

Team: Infrastructure Engineering / Monitoring Cloud

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.

Required Qualifications

• 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.

Why Join This Team?

You will be at the heart of Salesforce’s “Stability First” mission. This role offers the unique challenge of operating at massive scale while solving the intricate security puzzles of air-gapped infrastructure.You'll also be on the leading edge of AI-augmented infrastructure engineering, using AI on every inner-loop activity to deliver more per engineer than has ever been possible, while still owning the human-critical work (on-call, security, and customer outcomes) that defines great infr