Staff Engineer – GenAI Platforms & Agentic SDLC
Qualcomm
Role Overview
We are seeking a highly experienced Staff Engineer to drive the design, development, and scaling of GenAI-powered platforms, agentic workflows, and AI-native SDLC capabilities across CPSE. This role will be central to transforming GenAI from pilot initiatives into production-grade, enterprise-scale capabilities, enabling engineering teams to accelerate development, improve quality, and operationalize AI-driven workflows.
Minimum Qualifications:
- Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Software Engineering or related work experience.
OR
Master's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Software Engineering or related work experience.
OR
PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience.
- 2+ years of work experience with Programming Language such as C, C++, Java, Python, etc.
Key Responsibilities
- Platform, Skills & Integration Development - Design and build GenAI platform capabilities, including reusable AI skills and agents MCP servers and orchestration frameworks Tooling and integrations for internal platforms and enterprise data sources Ensure seamless integration with development, testing, and operational systems.
- Reusable Assets & Enterprise Adoption - Develop and curate reusable prompts, skills, and workflows to accelerate adoption across engineering teams. Establish validation frameworks to ensure quality, accuracy, and robustness of AI-driven assets. Drive standardization and reuse across teams and business units
- Enterprise AI Workflow Operationalization & Agentification - Lead the operationalization of QGenie-based workflows across CPSE use cases. Transform and agentify existing engineering workflows into scalable, reusable AI-driven solutions. Identify and prioritize high-impact workflows for automation and AI enablement across teams
- Agentic SDLC Transformation - Define and implement agent-driven SDLC workflows spanning: Coding and code generation Code review and validation Test automation and coverage Release and deployment orchestration Debugging and root-cause analysis Production monitoring and operations Enable end-to-end automation and intelligent orchestration across the SDLC lifecycle.
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