Senior Cloud Platform Engineer – SMTS

Salesforce

. Design and implement Terraform and Kubernetes automation frameworks for monitoring infrastructure .

Posted 9/18/2026full-timeBellevue • California • United StatesSenior💰 $148,500 - $223,900 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing Terraform and Kubernetes automation frameworks, managing infrastructure in AWS and GCP, and utilizing AI-assisted tooling for infrastructure as code. Proven ability to maintain observability and reliability in secure environments while addressing support requests with a customer-first mindset.

Highest-signal resume keywords

Terraform Automation FrameworksKubernetes ManagementAWS Infrastructure ManagementGCP Infrastructure ManagementAI-Assisted Development

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

TerraformKubernetesJavaPythonGrafanaKafkaElasticsearchCaching FrameworksAuthN/AuthZ Security ProtocolsInfrastructure Engineering

Soft Skills

Customer-First MindsetCritical EvaluationProblem-Solving

Tools & Technologies

Monitoring ToolsAI Coding AssistantsIncident Response Tools

Industry Keywords

Distributed SystemsAPI PlatformsObservabilityDevOpsOn-Call Rotation

Tech Stack

Tools & technologies

AWSCloudDistributed SystemsElasticSearchGoogle Cloud PlatformGrafanaJavaKafkaKubernetesPythonTerraform

About the role

Key responsibilities & impact

Design and implement Terraform and Kubernetes automation frameworks for monitoring infrastructure
Standardize paved-path deployments across AWS and GCP
Use AI-assisted tooling to author, refactor, and review IaC modules, Helm charts, and automation scripts
Own the Monitoring Cloud stack lifecycle, including version upgrades and performance tuning
Productize core components such as Grafana and custom Terraform providers for internal engineering teams
Deploy and manage monitoring stacks in highly isolated, air-gapped environments
Maintain observability and reliability for secure customer segments
Participate in the on-call rotation and maintain SLAs and availability targets
Conduct root-cause analysis for complex system failures and implement preventative fixes
Address support requests with a customer-first mindset
Use AI during incident response and RCA to summarize logs, correlate traces, propose hypotheses, and draft updates and postmortems
Design and deliver enterprise-grade platform features
Contribute to the team’s AI-assisted development playbook, including prompts, agents, skills, evaluation harnesses, and guardrails

Requirements

What you’ll need

5+ years of experience 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 such as Java and Python
Experience managing or extending monitoring tools such as Grafana
Experience with messaging systems such as Kafka
Experience with Elasticsearch
Experience with caching frameworks
Understanding of authN/authZ security protocols
Experience managing isolated or restricted network environments
Demonstrated use of AI coding assistants such as Claude Code in a daily engineering workflow
Ability to prompt effectively, critically evaluate generated code, and integrate AI into IaC, testing, and automation pipelines
Willingness and ability to participate in the team’s on-call rotation

Benefits

Comp & perks

Time off programs
Medical insurance
Dental insurance
Vision insurance
Mental health support
Paid parental leave
Life insurance
Disability insurance
401(k)
Employee stock purchasing program
Incentive compensation may be available
Equity may be available
Reasonable accommodation during the application or recruiting process