Site Reliability Engineer (SRE) - Regional Multi Project Platform

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

Equal Opportunity Employer Statement

Applicants: Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process.

Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. You may e-mail Ver el correo electrónico en click.appcast.io or call Qualcomm's toll-free number found here.

Qualcomm is also committed to making our workplace accessible for individuals with disabilities.