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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