Qualcomm
Designs, manufactures, and licenses wireless semiconductors
AI & Automation Lead Senior Staff Engineer - Software Engineering
About the job
- A bachelor's degree in Engineering, Information Systems, Computer Science, or a related field and 6 or more years of Software Engineering or related work experience; or a master's degree in those fields and 5 or more years of experience; or a PhD in those fields and 4 or more years of experience.
- At least 3 years of work experience with a programming language such as C, C++, Java, or Python.
- At least 15 years of experience in Software Validation, Firmware Validation, Software Quality Engineering, Test Automation, or related engineering disciplines.
- Experience designing and scaling automation frameworks, validation infrastructure, and large-scale testing solutions for embedded firmware.
- Proficiency in Python and/or C/C++ for automation, infrastructure, and tooling development.
- Hands-on experience with continuous integration and continuous delivery systems and automated validation pipelines.
- Demonstrated success leading cross-functional technical initiatives across multiple teams and projects.
- Experience applying Generative AI technologies to software engineering, quality engineering, or automation workflows.
- Hands-on experience leveraging large language models such as Claude, Gemini, OpenAI, or equivalent models for test generation, code analysis, or engineering automation.
- Experience building or integrating AI agents, autonomous workflows, or intelligent engineering systems.
- Familiarity with prompt engineering, AI evaluation techniques, and validation of AI-generated outputs.
- Define and execute the roadmap for AI adoption within Software Quality Engineering.
- Drive the use of Generative AI and autonomous systems to improve validation coverage, engineering productivity, defect discovery, and release confidence.
- Establish best practices for AI-assisted test development, validation workflows, and engineering automation.
- Identify opportunities to transform traditional validation processes through AI-driven solutions.
- Design and develop intelligent validation systems capable of generating, executing, analyzing, and maintaining test assets with minimal manual intervention.
- Leverage AI to automate test development, exploratory testing, coverage analysis, regression management, and defect triage.
- Develop scalable validation solutions that support complex software and firmware ecosystems across multiple product generations.
- Evaluate and integrate emerging AI technologies that deliver measurable engineering and quality benefits.
- Build AI-driven capabilities for failure triage, defect clustering, anomaly detection, quality trend analysis, and validation risk assessment.
- Develop intelligent systems that leverage logs, telemetry, crash data, and execution history to improve engineering decision-making and accelerate root-cause identification.
- Establish meaningful quality metrics and actionable insights that improve validation effectiveness and release readiness.
- Define the architecture and evolution of automation frameworks, validation platforms, and quality engineering infrastructure.
- Integrate AI-powered validation workflows into continuous integration and continuous delivery environments to deliver continuous quality feedback throughout the development lifecycle.
- Drive scalable automation solutions supporting functional, integration, performance, stress, stability, and system-level validation across multiple programs, architectures, and hardware generations.
- Serve as a technical leader for AI and automation initiatives across the broader quality engineering organization.
- Collaborate with software, firmware, systems, DevOps, and product teams to align validation strategies with business and release objectives.
- Mentor engineers in modern software quality practices, automation architecture, and AI-assisted engineering methodologies.
- Influence technical roadmaps, engineering standards, and investment decisions related to quality engineering and AI adoption.
- Prior experience with CPU/GPU validation, with a background in CPU program-level testing being advantageous.
- Experience validating firmware, platform software, systems software, embedded platforms, automotive platforms, datacenter/server products, or related technologies.
- Strong understanding of Windows and Linux-based development and validation environments.
- Familiarity with ARM64, x86, and/or RISC-V architectures.
- Experience with large-scale regression environments, telemetry systems, quality analytics platforms, and engineering observability solutions.
About the company
Qualcomm designs and licenses semiconductor technologies for wireless connectivity used in mobile devices, cars, and IoT. Its products include system-on-chips and RF components, plus a large portfolio of patents that it licenses to other companies. The company combines end-to-end semiconductor design with IP licensing to serve mobile, automotive, and IoT markets. Its goal is to expand wireless technology adoption by delivering standards-based silicon solutions and monetizing its intellectual property to support ongoing connectivity innovation.
Company Size
10,001+
Company Stage
IPO
Headquarters
San Diego, California
Founded
1985
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Simplify's Take
What believers are saying
- Amazon's September 8, 2026 pact targets up to $60 billion through 2036.
- Qualcomm's September 8, 2026 Dragonwing IQ-8275 Ubuntu certification strengthens industrial AI deployment.
- September 2026 Snapdragon X2 driver updates improve gaming compatibility across 22 titles.
What critics are saying
- Apple's modem exit accelerates in September 2026, cutting Qualcomm's highest-margin royalty stream.
- Amazon's custom-chip deal prices data-center growth below handset margins, pressuring 2027 profitability.
- NVIDIA, AMD, and internal hyperscaler silicon can sideline Qualcomm's fledgling data-center ambitions.
What makes Qualcomm unique
- Qualcomm owns cellular patents and modem silicon, anchoring handset licensing economics.
- Snapdragon X2 and Dragonwing pair power-efficient Arm compute with broad software certification.
- Amazon chose Qualcomm for multi-generation AI data-center silicon, validating hyperscaler-custom design.
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Benefits
Premium-free health coverage
Onsite health & fitness centers
Retirement programs
Disability & life insurance programs
Tuition reimbursement
Product discounts
Flexible time off
Parental leave
Growth & Insights and Company News
6 month growth
↑ 2%1 year growth
↑ 1%2 year growth
↑ 0%Qualcomm announced Tuesday that Amazon could purchase up to $60 billion of its server chips over the next decade. The companies will co-develop customised silicon for Amazon Web Services data centres, beginning with AI inference chips. This marks Qualcomm's second attempt at the server chip market. In 2017, the company launched its Centriq 2400 processor but shut down the business within a year after failing to secure volume orders. The data centre group shrank from over 1,000 employees to about 50 by late 2018. This time, Amazon's commitment includes binding purchase agreements. Qualcomm issued Amazon warrants for 25 million shares at $161.26, which vest based on executed commercial agreements and actual chip purchases capped at $60 billion through 2036.
BlueStacks, maker of the GamePop platform that streams Android games to televisions, has received $13 million in investment from Samsung. The funding reflects shared goals between the companies to expand mobile gaming experiences to other platforms. Intel, Qualcomm, Andreessen Horowitz and Redpoint also back the project, dubbed the "Netflix of games". BlueStacks CEO Rosen Sharma says they aim to bring popular mobile content to living rooms worldwide, noting a shift in gaming preferences among younger players. Last year, BlueStacks launched a compact "free version" of the device requiring a $7 monthly subscription. The Ouya competitor offers over 500 Android games. The original GamePop was discontinued shortly after the GamePop Mini launched.
Qualcomm has shifted its growth narrative away from laptop chips towards data centre revenue. The company nearly doubled its non-handset revenue target to $40 billion by fiscal 2029, with over $15 billion expected from data centres and more than $24 billion from automotive and IoT combined. The Snapdragon X Series for laptops, once a flagship product, now receives minimal mention in earnings calls. Instead, Qualcomm forecasts $5 billion in data centre revenue for fiscal 2027, starting with two custom silicon wins. Automotive remains a bright spot, with fiscal Q3 2026 sales reaching a record $1.6 billion, up 61% year over year. An expanded BMW partnership made Qualcomm the lead compute silicon provider for the carmaker's next-generation ADAS and digital cockpit systems.
Amazon announced a multigeneration partnership with Qualcomm to develop AI inference chips and optical networking technology capable of 1.6 terabits per second. The company's shares fell approximately 1.3% in early trading following the news. AWS generated $42.2 billion in second-quarter revenue, up 37%, with operating income reaching $16.6 billion. Amazon reported that both its chip franchise and broader AI business surpassed $25 billion in annual revenue run rates. Under the partnership, Qualcomm will help design Amazon hardware whilst using more AWS infrastructure and AI services for its own semiconductor development. AWS posted an operating margin of roughly 39.3%. The companies did not disclose pricing, purchase commitments, or a deployment timetable for the collaboration.
Qualcomm has struck a deal with Amazon to develop custom chips for AI data centres, issuing a warrant that gives Amazon the right to purchase approximately $4 billion in shares. The San Diego-based chipmaker's stock rose more than 7% in early trading following the announcement on Tuesday. The collaboration marks a significant partnership between the two companies in the AI infrastructure space. Custom chip development has become increasingly important as tech giants seek to optimise their data centre operations for artificial intelligence workloads.