Job Description

Locations

• San Francisco, California
• Bellevue, Washington

Salary

Skills Required

• a distinguished track record in performance engineering on technically demanding projectsIn-depthintermediate

Required Qualifications

• , business use cases, and to design appropriate performance/scalability simulations to measure and analyze performance and obtain insights into scalability and solve potential bottlenecks.Participate in discussions and planning with other members of the engineering and product teams.Design and implement scalability, stability, stress, reliability, availability, and longevity simulations for distributed systems using custom-developed software.Encourage sound design principles that result in optimal code and non-intrusive instrumentation.Champion the definition of appropriate SLIs/SLOs and service monitoring.Mentor engineers in the organization.Create and maintain robust load generation scripts and tools.Develop and automate performance and scale test suites.Perform deep-dive results analysis and profiling to identify root causes of performance regressions and bottlenecks across all layers of the stack, from frontend to backend systems.Debug complex performance and scale issues, utilizing profiling, tracing, Application Performance Monitoring (APM), metrics, and log instrumentation from various components such as browsers, networks, applications, caches, databases, and other critical distributed system elements.Provide actionable recommendations for optimizing performance, scalability, and availability issues.Implement and manage regression tracking for performance improvements.Prepare and deliver compelling performance readouts and presentations to stakeholders.Collaborate closely with development, QA, and operations teams to embed performance best practices throughout the software development lifecycle.Required Skills:Minimum of 8 years of relevant technical experience with a distinguished track record in performance engineering on technically demanding projectsIn-depth, hands-on experience in designing, implementing, testing, and providing production support for highly available, highly performant, and highly scalable multi-tenant distributed systems.Proven expertise in debugging performance and scale issues across the entire technology stack.Strong experience with profiling, tracing, APM tools, metrics, and log instrumentation.Proficiency in Kubernetes, autoscaling, and various cloud environments.Strong knowledge of Java, Python or Ruby, programming languages.Extensive experience with tools and technologies such as Splunk, Grafana, Prometheus, Kubernetes, Java, SQL, RDBMS, NoSQL Databases, and Linux.Strong understanding and experience with code reviews.Ability to debug complex scenarios and understand system design with an eye for performance and scalability bottlenecks with an aim to optimize code.Ability to automate operations such as simulation execution, monitoring, and analysis.Excellent communication skills both written and verbal with the ability to express clear thinking in words and technical documents.Solid understanding of database performance, such as SQL tuning and optimization.Experience in: operating system design/tuning/tools: Linux, containers / profiling tools: JFR, gprof, VTune, OProfile / load generation/measurement software and concepts: JMeter, or other custom load generation software) for HTTP, REST, RPC, and similar cloud systems/ database tuning and administration (e.g., Oracle).Familiarity with CI/CD pipelines and methodologies.A related technical degree required.Desired Skills:10+ years working on multiple releases with short cycles (3-6 months).Familiar with APM software.Familiar with database clustering/scaling technologies (e.g., RAC, Grid, OPS).Familiar with cloud-native architectures.Prior experience with Salesforce products is a plus.Knowledge and experience with AI/ML concepts and their application in performance engineering are highly desirable. For roles in San Francisco and Los Angeles: 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. (experience, 8 years)

Responsibilities

• Work closely with management, product owners, architects, developers, and quality engineers to understand product requirements, business use cases, and to design appropriate performance/scalability simulations to measure and analyze performance and obtain insights into scalability and solve potential bottlenecks.Participate in discussions and planning with other members of the engineering and product teams.Design and implement scalability, stability, stress, reliability, availability, and longevity simulations for distributed systems using custom-developed software.Encourage sound design principles that result in optimal code and non-intrusive instrumentation.Champion the definition of appropriate SLIs/SLOs and service monitoring.Mentor engineers in the organization.Create and maintain robust load generation scripts and tools.Develop and automate performance and scale test suites.Perform deep-dive results analysis and profiling to identify root causes of performance regressions and bottlenecks across all layers of the stack, from frontend to backend systems.Debug complex performance and scale issues, utilizing profiling, tracing, Application Performance Monitoring (APM), metrics, and log instrumentation from various components such as browsers, networks, applications, caches, databases, and other critical distributed system elements.Provide actionable recommendations for optimizing performance, scalability, and availability issues.Implement and manage regression tracking for performance improvements.Prepare and deliver compelling performance readouts and presentations to stakeholders.Collaborate closely with development, QA, and operations teams to embed performance best practices throughout the software development lifecycle.Required

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