Qualcomm India Private Limited has officially opened applications for the Engineer – AI Quality Assurance (QA) position at its Bengaluru engineering hub. This is a full-time, on-site opportunity for software engineers who want to work at the intersection of intelligent systems, enterprise-grade generative AI, and rigorous quality validation. If you have a background in software testing, API validation, and an interest in large language models or agentic application architectures, this role is worth your attention.
About Qualcomm
Qualcomm is one of the world’s leading semiconductor and wireless technology companies, consistently pushing the boundaries of mobile computing, connectivity, and artificial intelligence. Its engineering teams in India play a central role in developing next-generation software platforms that power devices and enterprise systems globally.
The Software Engineering Group at Qualcomm is actively building an enterprise-grade generative AI platform. This includes state-of-the-art agentic applications designed to accelerate productivity across all business units, alongside a robust infrastructure of Model SDKs, Frameworks, and Application APIs. Joining this team means working at the front line of the AI revolution, not as an observer but as a core contributor shaping how intelligent systems are tested, validated, and shipped at scale.
Job Overview
| Category | Details |
|---|---|
| Job Role | Engineer – AI Quality Assurance (QA) |
| Company | Qualcomm India Private Limited |
| Location | Bengaluru, Karnataka, India (On-site) |
| Employment Type | Full-time |
| Qualification | Bachelor’s degree in Engineering, CS, or Information Systems |
| Business Unit | Engineering Group, Software Engineering |
| Core Focus | Generative AI, SDK Validation, API Testing, Throughput Scaling |
Job Description
As an AI QA Engineer at Qualcomm, your role goes far beyond writing traditional test scripts. You will be responsible for designing, developing, and validating embedded and cloud edge software that powers some of the most advanced AI products available today.
The work involves tackling complex challenges around ultra-low latency, high-throughput scalability, and the seamless orchestration of on-premises and cloud-based data pipelines. You will collaborate closely with systems engineers, hardware architects, and test engineers to design robust, system-level validation solutions that ensure Qualcomm’s custom AI products meet stringent enterprise performance standards.
This is a role for engineers who think critically about AI output reliability, not just functional correctness, and who understand that validating a generative AI system requires a fundamentally different mindset than validating traditional software.
Key Responsibilities
Redefine AI Testing Move beyond traditional automation scripts to deeply validate the core logic, ethical safety guardrails, and output reliability of Generative AI systems. This includes testing for consistency, hallucination risk, and behavior under edge-case inputs.
SDK and API Validation Rigorously test and validate Model SDKs, Frameworks, and Application APIs that internal teams rely on to build custom AI solutions. Ensure that interfaces behave correctly, handle errors gracefully, and perform consistently across environments.
Performance Benchmarking Evaluate AI models and cloud edge software for ultra-low latency and high-throughput scalability. Design benchmarking frameworks that measure real-world performance under production-like conditions.
System Orchestration Testing Validate the orchestration logic and data pipeline flows between on-premises infrastructure and cloud-based systems. Ensure that handoffs between components are reliable, fault-tolerant, and performant.
Cross-Functional Collaboration Partner directly with systems engineers, hardware teams, and architects to gather performance requirements and co-design system-level test strategies. Clear communication across disciplines is essential in this role.
Quality Automation Create, modify, and maintain specialized utility programs that automate the QA lifecycle for state-of-the-art agentic applications. Automation here is not routine scripting; it requires judgment, creativity, and a deep understanding of how AI systems behave.
Skills and Eligibility Criteria
Educational Qualification A minimum Bachelor’s degree in Engineering, Information Systems, Computer Science, or a closely related technical field is required.
AI Literacy You should have a strong foundational understanding of Generative AI, Large Language Models (LLMs), and how agentic application architectures are structured and deployed.
Testing Expertise Proven experience in software quality assurance, API testing, and writing automation scripts is expected. Python is the highly preferred language for automation work in this role.
Performance Mindset Familiarity with testing highly scalable distributed systems, cloud and edge integrations, and latency benchmarking methodologies will set strong candidates apart.
Problem-Solving Ability Strong analytical skills are required to debug complex intelligent systems, trace failures through multi-component pipelines, and identify logic failures that only surface at edge cases.
Team Collaboration Excellent written and verbal communication skills are essential. You will regularly interface with diverse engineering groups and need to articulate QA findings clearly to both technical and non-technical stakeholders.
Why This Role Stands Out
AI quality assurance is one of the most rapidly evolving disciplines in software engineering. The shift from deterministic systems to probabilistic, generative ones has created entirely new categories of failure modes that traditional QA methodologies are not equipped to handle. Qualcomm is actively solving this problem at scale, and this role places you at the center of that effort.
Working within Qualcomm’s Software Engineering Group means access to some of the most advanced AI infrastructure being built today, a collaborative environment with hardware and systems engineers, and the opportunity to define what good looks like in AI testing for years to come.
For engineers who want their work to matter, who want to influence standards rather than just follow them, this position offers exactly that kind of scope.
How to Apply
Candidates are encouraged to apply through the official Qualcomm Careers portal. When preparing your application, make sure your resume clearly highlights:
- Your academic or professional background in software testing and QA
- Experience with API validation and automation scripting, particularly in Python
- Any exposure to Generative AI frameworks, LLM evaluation, or agentic system architectures
- Examples of performance testing or benchmarking work in distributed or cloud environments
The typical hiring process includes an initial coding and automation assessment, followed by technical interview rounds focused on system design for testing and AI logic validation.
Apply Now: Qualcomm Careers – Engineer AI QA, Bengaluru
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