The Site Reliability Engineer will design, analyze, and troubleshoot large-scale distributed systems, focusing on operating systems and performance tuning.
Job Description
Hello,
Greetings!
We have the following open position. If interested, please send us your resume along with all the details
Desired qualifications
• Expertise in designing, analyzing and troubleshooting large-scale distributed systems.
• In-depth knowledge of operating systems (processes, threads, concurrency issues, locks, mutexes, semaphores, monitors and how they work).
• Familiarity with algorithms, data structures and complexity analysis.
• Hands on Java and Apache optimization, performance tuning and configuration
• Systematic problem solving approach, coupled with a strong sense of ownership and drive.
Additional InformationNeed Locals
Intelliswift Santa Clara, California, USA Office
Santa Clara, CA, United States
Similar Jobs
Financial Services
Leads site reliability engineering for complex application and platform environments. Defines reliability requirements, observability strategies, service-level objectives, roadmaps, and production-readiness practices. Mentors engineers, debugs distributed systems, advances AI-assisted reliability workflows, and champions resilient, secure, auditable operations. Builds and oversees cloud-native infrastructure, APIs, event-driven systems, logging and monitoring pipelines, automation, and infrastructure-as-code solutions.
Top Skills:
Amazon SqsAutogenAWSAzureCassandraChaos MonkeyChromaCi/CdClaudeCrewaiDatadogDockerDynamoDBDynatraceFlinkFluentdGCPGithub CopilotGitopsGoGrafanaGremlinHadoopInfluxdbJavaKafkaKubernetesLangchainLanggraphLitmuschaosLogstashMcp ServersMongoDBNeo4JPineconePrometheusPythonPyTorchRabbitMQRestful ApisScikit-LearnSparkSplunkTensorFlowTerraformTigergraphTimescaledbVectorWeaviate
Artificial Intelligence • Professional Services • Business Intelligence • Consulting • Cybersecurity • Generative AI
Design, develop, deploy, monitor, and maintain AI-enabled enterprise and cloud security solutions. Build machine learning workflows, data pipelines, and scalable security capabilities using Python, Java, TensorFlow, and related libraries. Analyze security risks and data quality, translate technical findings into client recommendations, support security controls across cloud and infrastructure environments, review deliverables, and mentor junior team members.
Top Skills:
Artificial IntelligenceAWSCloud SecurityData PipelinesDatabricksEnterprise SecurityGCPJavaMachine LearningMachine Learning LibrariesAzurePythonSnowflakeTensorFlow
Cloud • Software
Lead the architecture, operation, and reliability of Cisco ThousandEyes’ FedRAMP-compliant AWS GovCloud platform. Build resilient cloud-native services using infrastructure as code, maintain high availability and security for high-volume data streams, automate compliance controls and auditing, and optimize multi-region infrastructure. Collaborate with engineering and security teams, lead technical initiatives, address operational risks, and establish engineering standards for regulated environments.
Top Skills:
AWSKubernetesPythonTerraform
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
