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About This Role
Company:
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Qualcomm Technologies, Inc.
Job Area:
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Engineering Group, Engineering Group \> Software Engineering
General Summary:
\*\* This position is not eligible for Qualcomm immigration sponsorship. \*\*
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Qualcomm is a world\-leading provider of mobile, computing, XR, automotive, and IoT SoCs and software technologies. Our Snapdragon platforms deliver highly integrated CPU/DSP/NPU capabilities that enable premium on\-device experiences with industry\-leading power efficiency.
As a member of Qualcomm’s Windows Audio Software team, you will design and build next\-generation on\-device Voice AI capabilities on Windows\-on\-Snapdragon platforms—spanning low\-power “always\-on” sensing through interactive speech experiences. You will collaborate with cross\-functional teams (hardware, DSP, systems, ML, and product) and work with global stakeholders across regions and sites to deliver robust, production\-ready solutions.
Responsibilities
- Own feature development end\-to\-end for Voice AI capabilities on Windows, including wake\-on\-voice , on\-device ASR , translation , transcription , and TTS .
- Gather and refine technical requirements with internal and external partners; translate product goals into clear engineering requirements, architecture, and milestones.
- Co\-design and implement Windows audio \+ driver stack solutions that leverage Qualcomm SoC CPU/DSP/NPU capabilities while meeting strict latency and power targets for Voice AI experiences.
- Build or extend components across user\-mode and kernel\-mode boundaries ( UMDF/KMDF ), integrating with Windows audio frameworks and platform services as needed for Voice AI pipelines.
- Drive low\-power audio architecture for “always\-on” use cases, including concurrency and power\-mode transitions across multiple audio features.
- Optimize and validate performance using Windows diagnostics and systematically debug complex multi\-threaded and multi\-processor issues across HW/SW boundaries.
- Communicate development status, risks, and mitigations to technical leads and stakeholders.
- Participate in roadmap planning and execution; contribute to process improvements that increase quality, scalability, and maintainability.
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.
Preferred Qualifications:
- Master's Degree in Engineering, Information Systems, Computer Science or related field.
- 3\+ years of industry experience in software engineering, with a focus in one or more of the following areas: Windows system software , device drivers, multimedia/audio, platform software, or performance/power\-sensitive products.
- Proficiency in systems programming (C/C\+\+ preferred) and ability to deliver production\-quality code in complex codebases.
- Strong Windows development skills using Visual Studio , source control (Git\-based workflows), and disciplined debugging practices.
- Solid understanding of Windows OS fundamentals relevant to system\-level development: processes/threads, synchronization primitives, memory, I/O, and performance diagnostics.
- Experience developing or integrating Windows drivers using KMDF and/or UMDF , including build, deployment, and debugging fundamentals.
- Hands\-on experience with multi\-threaded programming, concurrency control, and performance/latency tuning.
- Proven ability to work cross\-functionally and communicate effectively with distributed teams across regions/time zones.
- Windows audio ecosystem experience (any of the following): audio drivers, audio endpoints, WASAPI, audio effects/APOs, audio policy, power\-aware audio scenarios, or end\-to\-end audio pipeline integration.
- Demonstrated experience using AI\-assisted development tools to improve productivity across the software lifecycle (requirements/architecture, implementation, debugging, testing, and documentation), with the ability to iterate on prompts and validate outputs against real code and requirements.
- Familiarity with mainstream AI coding assistants (e.g., GitHub Copilot / Microsoft Copilot ) applied to practical engineering tasks such as code comprehension, change drafting, test scaffolding ideas, and documentation—while maintaining strong review and correctness discipline.
- Ability to create and share repeatable prompt patterns/templates for common engineering workflows and continuously refine prompts to increase specificity and accuracy.
- Experience with low\-power / always\-on audio and power\-state transitions (e.g., Modern Standby constraints and wake/trigger flows).
- Familiarity with on\-device voice activation building blocks and staged verification concepts (e.g., multi\-stage keyword/wake approaches).
- Experience optimizing workloads across heterogeneous compute ( CPU \+ DSP \+ NPU ) and understanding tradeoffs across latency vs. power vs. quality .
- Exposure to Voice AI pipelines: ASR/TTS, speech translation, transcription, streaming/buffering strategies, and real\-time constraints.
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\[email protected] 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).
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.
EEO Employer: Qualcomm is an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other protected classification.
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.
Pay range and Other Compensation \& Benefits :
$111,300\.00 \- $166,900\.00
The above pay scale reflects the broad, minimum to maximum, pay scale for this job code for the location for which it has been posted. Even more importantly, please note that salary is only one component of total compensation at Qualcomm. We also offer a competitive annual discretionary bonus program and opportunity for annual RSU grants (employees on sales\-incentive plans are not eligible for our annual bonus). In addition, our highly competitive benefits package is designed to support your success at work, at home, and at play. Your recruiter will be happy to discuss all that Qualcomm has to offer – and you can review more details about our US benefits at this link .
If you would like more information about this role, please contact Qualcomm Careers .
Salary Context
This $111K-$166K range is in the lower quartile for AI Software Engineer roles in our dataset (median: $190K across 219 roles with salary data).
Role Details
About This Role
AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.
The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.
Across the 3,823 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Qualcomm, this role fits into their broader AI and engineering organization.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
What the Work Looks Like
A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
Skills Required
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.
Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
Compensation Benchmarks
AI Software Engineer roles pay a median of $232,000 based on 797 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($139K) sits 40% below the category median. Disclosed range: $111K to $166K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Qualcomm AI Hiring
Qualcomm has 6 open AI roles right now. They're hiring across AI/ML Engineer, Research Engineer, LLM Engineer, AI Software Engineer. Positions span San Diego, CA, US, Santa Clara, CA, US. Compensation range: $166K - $244K.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 median).
Career Path
Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.
From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.
If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.
What to Expect in Interviews
Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.
When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
AI Hiring Overview
The AI job market has 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 roles).
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
The AI Job Market Today
The AI job market spans 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (112) are outnumbered by mid-level (1,798) and senior (1,516) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $275,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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