Site Reliability Engineer (SRE) – Regional Multi Project Platform

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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