Site Reliability Engineer - Multiple Teams

Company:

QUALCOMM SEMICONDUCTORES Y SISTEMAS AVANZADOS DE BAJA CALIFORNIA

Job Area:

Engineering Group, Engineering Group > Software Engineering

General Summary:

Cloud Infrastructure & Infrastructure as Code

• Design, build, and manage cloud infrastructure with a primary focus on AWS, integrated with OpenStack environments
• Build and maintain Infrastructure as Code using:
  • Terraform
  • Ansible
  • Kubernetes (manifests / Helm)

• Design infrastructure solutions for:
  • Scalability
  • High availability
  • Performance
  • Reliability
  • Cost efficiency

• Implement redundancy, failover, and disaster‑recovery patterns across services and regions
• Perform capacity planning based on performance metrics, usage trends, and utilization data

Kubernetes & Platform Reliability

• Operate and scale production Kubernetes clusters in large‑scale environments
• Partner with development and QA teams to:
  • Improve system reliability and resiliency
  • Automate scalability and availability mechanisms

• Apply SRE principles including:
  • Service reliability ownership
  • Proactive failure prevention
  • Continuous improvement of operational processes

• Support microservices‑based and distributed system architectures

CI/CD, Automation & Operational Excellence

• Manage and evolve CI/CD pipelines (e.g., Jenkins)
• Automate infrastructure provisioning, configuration, and lifecycle management
• Write, maintain, and improve runbooks for operational processes
• Build automation to reduce manual intervention and operational toil
• Plan and execute infrastructure upgrades and maintenance activities
• Proactively identify and address technical and infrastructure debt

Data Platforms & Streaming Systems

• Operate, tune, and scale data and streaming platforms, including:
  • Kafka, Zookeeper
  • NiFi
  • Elasticsearch
  • MySQL, Vertica

• Diagnose and resolve performance and stability issues across data pipelines
• Ensure data platform reliability, throughput, and resilience at scale

AI‑Assisted SRE & Intelligent Automation

• Design and maintain knowledge‑driven automated runbooks and operational bots
• Develop AI‑assisted operational workflows, including:
  • Incident analysis and summarization
  • Intelligent diagnostics and remediation suggestions
  • Automation of repetitive operational decision‑making

• Work with LLM‑based agent frameworks (e.g., Claude Agent SDK or similar):
  • Integrate agents with logs, metrics, monitoring, and internal tools
  • Implement guard‑railed, controlled‑action automation for production use

• Research and propose new concepts, tools, and AI‑driven approaches to improve reliability and efficiency

Monitoring, Reliability & Incident Management

• Design and operate monitoring and observability systems using:
  • Prometheus
  • Grafana
  • ELK stack

• Improve alert quality, signal‑to‑noise ratio, and troubleshooting efficiency
• Lead incident response activities, root cause analysis, and post‑incident reviews
• Support software engineers in debugging complex production issues across distributed systems
• Embed reliability, automation, and operational readiness into system design

Experience Required

• Extensive experience operating large‑scale distributed cloud systems
• Hands‑on experience with AWS in production environments
• Direct experience working with OpenStack
• Strong Linux background in large‑scale SaaS or production systems
• Ability to:
  • Maintain and improve existing mission‑critical systems
  • Prioritize and systematically reduce technical and infrastructure debt

• Strong understanding of designing for operational excellence, not just greenfield solutions

Required Skills

• Programming: Strong experience with Python and/or Go
• Cloud & IaC: Terraform, Ansible, CloudFormation or equivalent
• Containers: Kubernetes (production experience)
• CI/CD: Jenkins and modern CI/CD practices
• Data & Streaming: Kafka, NiFi, Elasticsearch, MySQL, Vertica, Zookeeper
• Observability: Prometheus, Grafana, ELK
• Infrastructure: Nginx, Linux internals
• AI / Automation (advantage):
  • Experience integrating AI or LLMs into operational workflows
  • Familiarity with agent‑based automation concepts

Experience Guidelines

3+ years in:

• overall experience managing infrastructure
• Linux administration in large‑scale environments
• operating production systems on AWS and/or OpenStack
• managing Kubernetes in production
• using infrastructure as code
• working with CI/CD systems

Minimum Qualifications:

•    Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience.
OR
Master's degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Software Engineering or related work experience.
OR
PhD in Engineering, Information Systems, Computer Science, or related field.

• 2+ years of academic or work experience with Programming Language such as C, C++, Java, Python, etc.

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