Sr. Lead/Sr. Engineer- Enterprise AI Platform

Job description

**General Summary:** As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drives digital transformation to help create a smarter, connected future for all. As a Qualcomm Software Engineer, you will design, develop, create, modify, and validate embedded and cloud edge software, applications, and/or specialized utility programs that launch cutting-edge, world class products that meet and exceed customer needs. Qualcomm Software Engineers collaborate with systems, hardware, architecture, test engineers, and other teams to design system-level software solutions and obtain information on performance requirements and interfaces. Join the team building Qualcomm's Enterprise-Grade Generative AI Platform. We are at the forefront of the AI revolution, developing State-of-the-Art (SOTA) agentic applications designed to hyper-charge productivity across all Qualcomm business units. Our mission extends beyond internal tools; we are building a robust infrastructure by exposing Model SDKs, Frameworks, and Application APIs that empower other teams to build their own custom AI solutions. We operate at scale, solving complex challenges related to ultra-low latency, high-throughput scalability, and the seamless orchestration of on-premises and cloud-based data 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. - Master's degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Software Engineering or related work experience. - PhD in Engineering, Information Systems, Computer Science, or related field. - 2+ years of academic or work experience with programming languages such as C, C++, Java, Python, etc. As a Platform Engineer, you will build the backbone of our AI ecosystem, ensuring our data pipelines and services are robust, scalable, and efficient. - Focus: Infrastructure, Data Engineering, and Scalable Backend Systems **Key Responsibilities:** - Develop and modify specialized utility programs and general applications to optimize operational efficiency. - Design and manage large-scale data warehouses and build complex ETL pipelines. - Bridge the gap between on-premises data and AWS-based cloud pipelines (SageMaker, Glue, Athena). - Optimize system performance to meet stringent latency and scalability requirements for global enterprise use. **Requirements:** - Experience: 3-7 years in ML Engineering, Data Engineering, or Software Development. - Technical Stack: Solid experience with Python, SQL, and AWS analytical technologies (Glue, Athena, QuickSight, SageMaker). - Big Data: Proficiency in data modeling, warehousing, and handling large-scale data exchange formats. - Education: Bachelors in CS/Engineering; Masters with a focus on Data Science/ML is a plus.