Senior DevOps Engineer/IT Engineer

Company
Qualcomm Intl Inc., Mexico Branch Office

Job Area
Information Technology Group, Information Technology Group > IT Engineering

General Summary
As a Senior Linux Systems Engineer within the HW Engineering Compute team, you will be responsible for the health, performance, and scalability of massive-scale compute environments that power Qualcomm’s next-generation semiconductor design. This will relate to management, configuration, and augmentation of the HPC servers leveraged to enable Qualcomm’s Electronic Design Automation (EDA) workloads both on-premises and in public cloud.

Our
Hybrid Cloud strategy
will require maintenance and evolution of our current cloud footprint for "bursting" of workloads from on-premises data centers to major public cloud providers. This includes optimizing for both cost and performance within the unique context of that environment.

Key Responsibilities

• Provide expert-level administration for enterprise Linux distributions including RHEL, Rocky Linux, Ubuntu and SLES.
• Unify infrastructure using configuration management to ensure configuration parity between on-prem and cloud environments.
• Develop script-based automations to facilitate "passive" knowledge capture, transcribing triage sessions into structured workflows that can be applied to future cloud-scale issues.
• Architect and maintain Cloud Bursting solutions that allow on-premises HPC schedulers (Slurm/LSF) to dynamically scale into public cloud environments.
• Optimize cloud instance selection for specific EDA tool behaviors (e.g., memory-intensive synthesis vs. compute-heavy simulation), focusing on HPC-optimized instances and specialized networking (e.g., AWS EFA).
• Implement cost-governance strategies for cloud compute to minimize waste without impacting engineering schedules.
• Utilize observability tools to monitor workloads, identifying bottlenecks in on premises workloads or the cloud
• Understand key facilities within the Linux OS to improve EDA tool performance
• Understand how to interact with HPC job schedulers (Slurm, PBS, or LSF) to ensure high throughput and fair resource allocation for massive EDA workloads.

Qualifications
Minimum Qualifications

• Education: Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related STEM field.
• Experience: 3+ years of direct Linux system administration experience.
• Cloud: Experience deploying and managing Linux-based workloads in at least one major public cloud provider (AWS, Azure, or GCP).

Preferred Qualifications

• EDA Experience: Familiarity with the compute requirements of EDA tools (e.g., Cadence, Synopsys, Mentor Graphics).
• Cloud HPC: Experience with cloud-native HPC tools like AWS Parallel Cluster, Azure CycleCloud, or cloud-based NetApp/Lustre storage.
• IaC Mastery: Advanced proficiency with Terraform for multi-cloud infrastructure deployment.
• Certification: AWS Certified SysOps Administrator, Azure Administrator Associate, or equivalent GCP certification.

Minimum Qualifications

• 3+ years of IT-related work experience with a Bachelor's degree.

OR

5+ years of IT-related work experience without a Bachelor’s degree.

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. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries).

Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.

To all Staffing and Recruiting Agencies
: Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications.

If you would like more information about this role, please contact Qualcomm Careers.

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Azure DevOps Engineer Pay Rate: $22.50-$30/hour Role Summary

The primary mandate of this role is to ensure production systems remain performant, healthy, secure, and reliable, with database and application performance serving as top priorities. This responsibility is supported through DevOps practices, including CI/CD, infrastructure as code, and deployment automation, as well as Site Reliability Engineering (SRE) ownership of observability, alerting, scalability, and incident prevention.

This individual will play a key role in driving the organization's on-premises to cloud migration strategy while improving the resilience, redundancy, and scalability of its platform. Operating within a product-focused and highly regulated environment, the ideal candidate values practical, proven solutions, prioritizing system stability, data integrity, and operational excellence over adopting technology trends for their own sake.

Key Responsibilities Production Performance & Reliability

• Serve as the primary owner of production system health, availability, and performance.
• Build, maintain, and scale highly available production environments supporting APIs, services, and business-critical applications.
• Design and implement resilient architectures with redundancy, failover capabilities, and zero-downtime deployment strategies.
• Develop and enhance observability capabilities across infrastructure, networks, databases, and applications through centralized metrics, logs, and distributed tracing.
• Establish proactive monitoring and alerting frameworks to identify and resolve issues before customer impact occurs.
• Generate operational and SLA reporting for business and technical stakeholders.
• Diagnose and resolve database, infrastructure, and network performance issues, including SQL Server query optimization, indexing strategies, and execution plan analysis.

Scalability & Capacity Planning

• Design and implement horizontal and vertical scaling strategies for APIs, web services, and database platforms.
• Conduct load, stress, and performance testing to validate scalability assumptions and identify bottlenecks.
• Partner with engineering teams to support capacity planning and growth initiatives across production workloads.

Infrastructure & Cloud Operations

• Provision, manage, and optimize Azure cloud infrastructure using Terraform and infrastructure-as-code best practices.
• Administer cloud networking and security components, including VNets, VPN connectivity, Web Application Firewalls (WAFs), Network Security Groups (NSGs), and related controls.
• Maintain development, test, staging, and production environments while ensuring configuration consistency and operational health.

Deployment & Release Engineering

• Support, optimize, and troubleshoot CI/CD pipelines used for .NET/C# application delivery.
• Improve deployment automation, release reliability, and operational efficiency across development and production environments.

Cloud Migration & Modernization

• Lead the migration of on-premises applications and infrastructure to Microsoft Azure as part of the organization's cloud transformation strategy.
• Assess existing dependencies and recommend appropriate modernization, cloud-native, or lift-and-shift approaches.
• Support the implementation of hybrid-cloud architectures where appropriate.

Required Experience & Qualifications

• 7+ years of experience in DevOps, Site Reliability Engineering (SRE), cloud infrastructure, or related disciplines supporting production environments.
• 10+ years of relevant experience preferred.
• Demonstrated success owning production system performance, availability, and operational health.
• Experience managing infrastructure and services against defined uptime, reliability, and SLA commitments.
• Strong SQL Server administration, performance tuning, and query optimization expertise.
• Hands-on experience with CI/CD platforms and deployment tooling such as Azure DevOps, GitHub Actions, Jenkins, or similar technologies.
• Strong experience with Microsoft Azure services, including compute, networking, security, monitoring, and automation capabilities.
• Proficiency with Terraform and infrastructure-as-code methodologies.
• Experience designing and supporting serverless, containerized, and cloud-native solutions using Azure services such as Azure Functions, App Services, Container Apps, and Logic Apps.
• Solid understanding of cloud networking and security fundamentals, including VPNs, VNets, WAFs, NSGs, TLS, and related technologies.
• Experience implementing scalable, resilient, and highly available distributed systems.
• Hands-on experience with API load and performance testing tools such as k6, JMeter, Azure Load Testing, or equivalent.
• Experience implementing observability and monitoring solutions utilizing Azure Monitor, Application Insights, Grafana, Prometheus, or similar platforms.

Preferred Qualifications

• Microsoft Azure certifications such as AZ-104, AZ-305, AZ-400, or equivalent.
• Experience supporting hybrid cloud environments and large-scale cloud migration initiatives.
• Experience working within distributed, nearshore, or globally distributed engineering teams.
• Experience supporting organizations operating in highly regulated industries.

Only applications of candidates with Mexican citizenship will be evaluated for this role in compliance with the provisions of Article 7 of the Federal Labor Law.

Please submit your resume in English - we can only consider applications submitted in this language.
Minimum qualifications:

• Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
• 5 years of experience with software development using Python or similar coding languages.
• Experience architecting AI systems on cloud platforms (e.g., Google Cloud Platform).
• Experience building pipelines for structured and unstructured data using both vector databases and Retrieval-augmented generation (RAG)-like architectures to power enterprise AI solutions.
• Experience taking production-grade AI-driven solutions from conception to launch for customers.
• Ability to communicate in English and Spanish fluently to support client relationship management in this region.

Preferred qualifications:

• Master’s degree or PhD in AI, Computer Science, or a related technical field.
• Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, ADK) and complex patterns (e.g., ReAct, self-reflection, hierarchical delegation).
• Knowledge of "Large Language Models (LLMs)-native" metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.

About the job
As a GenAI Forward Deployed Engineer (FDE) at Google Cloud, you are an embedded builder who bridges the gap between frontier AI products and production-grade reality within customers. Unlike traditional advisory roles, you function as an "innovator-builder," moving beyond high-level architecture to code, debug, and jointly ship bespoke agentic solutions directly within the customer’s environment. This role is designed for high-agency engineers with a founder’s mindset. You will address blockers to production including solving the integration complexities, data readiness issues, and state-management challenges that prevent AI from reaching enterprise-grade maturity. By embedding with strategic accounts, you serve a dual purpose: providing "white glove" deployment of complex AI systems and acting as a critical feedback loop, transforming real-world field insights into Google Cloud’s future product roadmap.It's an exciting time to join Google Cloud’s Go-To-Market team, leading the AI revolution for businesses worldwide. You’ll excel by leveraging Google's brand credibility—a legacy built on inventing foundational technologies and proven at scale. We’ll provide you with the world's most advanced AI portfolio, including frontier Gemini models, and the complete Vertex AI platform, helping you to solve business problems. We’re a collaborative culture providing direct access to DeepMind's engineering and research minds, empowering you to solve customer challenges. Join us to be the catalyst for our mission, drive customer success, and define the new cloud era—the market is yours.

Responsibilities

• Serve as a developer for complex AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, MCP servers) that drive measurable return on investment.
• Architect and code the "connective tissue" between Google’s AI products and customer's live infrastructure, including APIs, legacy data silos, and security perimeters as part of an expert team.
• Build high-performance evaluation pipelines and observability frameworks to ensure agentic systems meet the requirements for accuracy, safety, and latency.
• Identify repeatable field patterns and friction points in Google’s AI stack, converting them into reusable modules or formal product feature requests for the Engineering teams.
• Co-build with customer engineering teams to instill Google-grade development best practices, ensuring long-term project success and high end-user adoption.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form .

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.

Lyft is a global company that connects people to transportation to change the way we live and get around our communities. Our drivers and passengers entrust Lyft with their personal information and travel details to get where they are going and expect us to keep that data safe. Lyft's Privacy team is composed of engineers and analysts dedicated to ensuring appropriate data protections are applied to our drivers' and passengers' data. Our goal is to make privacy the default setting for our internal engineers and our customers. We help design architectures, build a scalable data platform, and define policies to reduce the exposure of user data and ensure appropriate privacy and security protections are applied across the company.

We are looking for a highly motivated, collaborative, team-focused and technically strong Senior Software Engineer to join our Privacy team. As a member of this team, you will design and build systems that make privacy the default at Lyft. Every day, you'll partner with engineering, product, legal, and compliance stakeholders on high-impact projects — from building data redaction pipelines to enabling users to exercise their privacy rights to deploying data management systems across a diverse set of Lyft services. You'll bring strong engineering instincts, a passion for privacy, and the ability to lead large projects from idea to execution.

Responsibilities:

• Design, build, and maintain systems that enhance privacy across the organization
• Independently lead large projects from idea to execution
• Advocate for user privacy throughout the organization, consulting engineering teams throughout the software development lifecycle and escalating potential privacy concerns
• Write well-crafted, well-tested, readable, and maintainable code
• Participate in code reviews to ensure code quality and distribute knowledge
• Share knowledge by giving brown bags, tech talks, and championing appropriate tech and engineering best practices
• Contribute to the development of controls and continuous testing, and design remediation and risk mitigation solutions
• Partner closely with cross-functional stakeholders to enable privacy by design in our products, services, and business processes
• Anticipate problems and proactively suggest architectural improvements to stay ahead

Experience:

• 5-7 years of experience in software engineering
• Proficiency in at least one general-purpose programming language (e.g., Python, Java, Go)
• Experience in operational and analytical data systems (e.g., DynamoDB, Aurora, Redis, Databricks, etc.)
• Skills in scripting languages (Python, Ruby, Bash)
• Proficient in at least one query language (SQL, Cypher, MQL, PL/SQL)
• Experience developing distributed systems
• Experience working with cross-functional stakeholders (Compliance, Legal, Product, Infrastructure)
• Ability to learn and research new technologies rapidly, analyze systems for privacy impact, and build scalable solutions to tackle problems
• Ability to write thorough, scalable, and clear design documentation
• Ability to own and manage high priority projects and multiple tasks
• Excellent written and verbal communication skills and a love for documentation and collaboration
• Experience mentoring junior engineers through code reviews and project task breakdown, scoping, and sequencing
• Experience using AI-assisted development tools responsibly (e.g. GitHub Copilot, Cursor, AI agents), or experience building privacy-aware AI/ML systems
• Experience in working through ambiguity, developing deployable solutions to complex problems
• Preferred qualifications

• 2-3 years of experience working with privacy/security services
• Experience working with ETL tools (Airflow, Spark, Jupyter Notebooks)
• Familiar with CCPA, GDPR and other privacy regulations
• Experience with automation and creating tools for a distributed systems

Please submit your resume in English.