Production Support Engineering - Cloud DevOps Engineer
Compensation
Not disclosed
Location
San Francisco, CA, US
Work setup
Not specified
Seniority
Lead
Employment
Full time
Experience
6+ years
Category
Devops
Posted
Skills
agentforce
agentic-ai
agile
ai
ansible
api
automation
aws
azure
candidate-experience
ci-cd
cloud
cloud-native
cloud-security
cloudformation
containerization
crm
devops
distributed-systems
docker
gcp
grafana
hbase
helm
iam
infrastructure-as-code
java
kubernetes
linux
networking
observability
oop
opentelemetry
oracle
postgresql
prometheus
python
salesforce
secrets-management
splunk
sre
terraform
vulnerability-management
Must have
6+ years of experience in a senior or lead role in Cloud DevOps engineering.
Experience in performance engineering and benchmarking.
Experience designing, deploying, or operating production workloads on public cloud platforms such as AWS, Azure, or Google Cloud Platform.
Experience developing production software in Core Java, Python, or another object-oriented programming language.
Strong understanding of cloud infrastructure concepts, including compute, storage, networking, load balancing, identity and access management, security, high availability, and disaster recovery.
Experience with containerization and cloud-native technologies such as Docker, Kubernetes, or comparable container orchestration platforms.
Experience with Infrastructure as Code and configuration automation using tools such as Terraform, CloudFormation, Ansible, Helm, or comparable tooling.
Experience building, maintaining, or improving CI/CD pipelines and automated build, test, deployment, and release workflows.
Development or automation experience using Python, Go, Java, or another programming language. You can build maintainable, production-quality automation, tools, services, or APIs.
Familiarity with databases (Postgres, HBase, Oracle, or similar) and database cluster technologies such as Oracle RAC (Real Application Clusters).
Experience with Linux systems and working knowledge of operating systems, networking, process, memory, storage, and performance fundamentals.
Experience with production observability using logs, metrics, traces, dashboards, and alerting platforms.
Nice to have
Experience operating large-scale distributed systems or high-availability production platforms.
Experience with Kubernetes ecosystem technologies, service discovery, ingress, service mesh, autoscaling, or container platform engineering.
Experience building internal developer platforms, self-service infrastructure, deployment frameworks, or operational automation.
Experience with Site Reliability Engineering (SRE) practices, including service level objectives (SLOs), service level indicators (SLIs), error budgets, capacity management, and incident management.
Experience with cloud security, IAM, secrets management, vulnerability management, policy enforcement, and infrastructure security controls.
Experience with observability technologies such as Prometheus, Grafana, OpenTelemetry, Splunk, or comparable platforms.
Experience with databases, caching systems, messaging platforms, or distributed data infrastructure.
Familiarity with multi-region, multi-cloud, disaster recovery, or large-scale cloud migration architectures.
Familiarity with Agile development practices and iterative release cycles.
Full description
Production Support Engineering - Cloud DevOps Engineer SMTS
Location: California - San Francisco
Remote Type: Office Tech-Flexible
Time Type: Full time
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.
Role Description
We are looking for a Cloud & DevOps Engineer, Senior Member of Technical Staff (SMTS), to design, build, automate, and operate reliable, secure, and scalable cloud infrastructure and production platforms. You will work with software engineers, infrastructure teams, security partners, and product teams. Your work will improve service availability, deployment reliability, operational efficiency, and developer productivity.
The ideal candidate has strong experience with public cloud and cloud-native technologies, infrastructure automation, CI/CD, observability, and production operations. They also have practical software development experience in Python, Java, Go, or another programming language. This is an engineering-focused DevOps role. We expect automation and software development to replace repetitive manual operations.
You approach ambiguous infrastructure and production problems methodically. You understand system behavior across application and infrastructure layers. You use modern engineering practices, including AI-assisted development, to improve reliability, automation, and delivery effectiveness.
Required Qualifications
6+ years of experience in a senior or lead role in Cloud DevOps engineering.
Experience in performance engineering and benchmarking.
Experience designing, deploying, or operating production workloads on public cloud platforms such as AWS, Azure, or Google Cloud Platform.
Experience developing production software in Core Java, Python, or another object-oriented programming language.
Production Support Engineering - Cloud DevOps Engineer at Salesforce: The #1 AI CRM (San Francisco, CA, US) — aijobsearch
Understanding of distributed-system and reliability concepts, including scalability, fault tolerance, resiliency, service dependencies, capacity, availability, and performance.
Experience troubleshooting complex production issues across application, infrastructure, networking, and cloud layers.
Experience working across the software and infrastructure delivery lifecycle: design, implementation, testing, deployment, monitoring, incident response, and continuous improvement.
Experience using AI-assisted development tools or techniques for automation, software development, troubleshooting, testing, debugging, or documentation.
Strong analytical and problem-solving skills, including the ability to diagnose complex infrastructure and production problems systematically.
Effective written and verbal communication skills and the ability to collaborate across engineering and operational teams.
Strong understanding of cloud infrastructure concepts, including compute, storage, networking, load balancing, identity and access management, security, high availability, and disaster recovery.
Experience with containerization and cloud-native technologies such as Docker, Kubernetes, or comparable container orchestration platforms.
Experience with Infrastructure as Code and configuration automation using tools such as Terraform, CloudFormation, Ansible, Helm, or comparable tooling.
Experience building, maintaining, or improving CI/CD pipelines and automated build, test, deployment, and release workflows.
Development or automation experience using Python, Go, Java, or another programming language. You can build maintainable, production-quality automation, tools, services, or APIs.
Familiarity with databases (Postgres, HBase, Oracle, or similar) and database cluster technologies such as Oracle RAC (Real Application Clusters).
Experience with Linux systems and working knowledge of operating systems, networking, process, memory, storage, and performance fundamentals.
Experience with production observability using logs, metrics, traces, dashboards, and alerting platforms.
Understanding of distributed-system and reliability concepts, including scalability, fault tolerance, resiliency, service dependencies, capacity, availability, and performance.
Experience troubleshooting complex production issues across application, infrastructure, networking, and cloud layers.
Experience working across the software and infrastructure delivery lifecycle: design, implementation, testing, deployment, monitoring, incident response, and continuous improvement.
Experience using AI-assisted development tools or techniques for automation, software development, troubleshooting, testing, debugging, or documentation.
Strong analytical and problem-solving skills, including the ability to diagnose complex infrastructure and production problems systematically.
Effective written and verbal communication skills and the ability to collaborate across engineering and operational teams.
Preferred Qualifications
Experience operating large-scale distributed systems or high-availability production platforms.
Experience with Kubernetes ecosystem technologies, service discovery, ingress, service mesh, autoscaling, or container platform engineering.
Experience building internal developer platforms, self-service infrastructure, deployment frameworks, or operational automation.
Experience with Site Reliability Engineering (SRE) practices, including service level objectives (SLOs), service level indicators (SLIs), error budgets, capacity management, and incident management.
Experience with cloud security, IAM, secrets management, vulnerability management, policy enforcement, and infrastructure security controls.
Experience with observability technologies such as Prometheus, Grafana, OpenTelemetry, Splunk, or comparable platforms.
Experience with databases, caching systems, messaging platforms, or distributed data infrastructure.
Familiarity with multi-region, multi-cloud, disaster recovery, or large-scale cloud migration architectures.
Familiarity with Agile development practices and iterative release cycles.
Responsibilities
Design, build, automate, and operate secure, reliable, and scalable cloud infrastructure and production platforms.
Independently deliver well-scoped cloud, DevOps, reliability, and automation improvements after alignment on the overall technical plan and architecture.
Develop software, automation frameworks, scripts, APIs, and engineering tools in Python, Go, Java, or comparable languages. These reduce manual operations and improve platform reliability.
Build and maintain Infrastructure as Code for repeatable provisioning, configuration, deployment, and lifecycle management of cloud resources.
Develop and improve CI/CD pipelines that automate build, testing, security validation, deployment, rollback, and release processes.
Deploy and operate containerized workloads using Kubernetes or comparable cloud-native platforms.
Apply cloud and distributed-systems concepts such as scalability, fault tolerance, service communication, networking, availability, resiliency, and capacity management.
Build and improve observability using metrics, logs, traces, dashboards, alerts, and health checks. These give the team actionable visibility into production systems.
Diagnose production incidents using telemetry and system-level analysis. Identify contributing factors and root causes, and implement improvements that prevent recurrence.
Identify repetitive operational activities and convert them into safe, testable, and maintainable automation.
Participate in production support and incident response. This includes troubleshooting complex issues across application, cloud, Kubernetes, networking, storage, and infrastructure layers.
Contribute to infrastructure and platform design discussions, identify implementation and operational tradeoffs, and seek guidance when decisions have broader architectural, security, or product impact.
Apply security and reliability practices throughout infrastructure and software delivery, including access controls, secrets management, change validation, testing, rollback, and deployment safeguards.
Participate in the full engineering lifecycle: requirements refinement, design, development, code review, testing, deployment, monitoring, production support, and operational improvement.
Use AI-assisted development tools responsibly to accelerate automation and engineering work, improve code and configuration quality, assist troubleshooting and testing, and increase team effectiveness. Apply appropriate security and quality controls.
Collaborate effectively with software engineers, infrastructure teams, security teams, and other cross-functional partners. Communicate technical and operational decisions clearly, and contribute to engineering documentation and runbooks.
Unleash Your Potential
When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best, and our AI agents accelerate your impact so you can do your best. Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future — but to redefine what’s possible — for yourself, for AI, and the world.
Accommodations
If you need a reasonable accommodation during the application or the recruiting process, please submit a request via this Accommodations Request Form.
Please note that Salesforce uses artificial intelligence (AI) tools to help our recruiters assess and evaluate candidates’ resumes and qualifications throughout the recruiting process. Humans will always make any candidate selection and hiring decisions. Please see our Candidate Privacy Statement for more information about how we use your personal data and your rights, including with regard to use of AI tools and opt out options.
Posting Statement
Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, 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.
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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.