Principal, Gen AI Transformation - Embedded Software & Engineering Productivity

Company:Qualcomm Technologies, Inc.
Job Area:Engineering Group, Engineering Group >
Software Engineering

General

Summary:

Team SPARK is leading the Generative AI transformation across CPSG, spanning embedded software, platform systems, product enablement, and engineering infrastructure. We are seeking a Principal Engineer to define and scale AI-first engineering practices that improve developer productivity, software quality, delivery velocity, and innovation. This is a high-impact technical leadership role for a hands-on, systems-minded GenAI leader who can translate emerging AI capabilities into secure, measurable, production-grade engineering workflows.

You will partner across SPARK, central GenAI platform teams, and engineering teams to shape strategy, build reusable AI assets, and accelerate adoption at organizational scale.

Key Responsibilities

• Define and drive the GenAI transformation roadmap for engineering productivity across CPSG, with clear priorities, adoption plans, and measurable outcomes.
• Lead AI-native and agentic SDLC initiatives across requirements, code understanding, code generation, code review, debugging, test automation, release readiness, and documentation.
• Partner with GenAI platform and engineering teams to build reusable agents, skills, tools, plugins, MCP integrations, and governed workflow patterns.
• Identify high-value embedded and software workflows, turn them into reusable capabilities, and scale adoption across teams to reduce duplication and increase leverage.
• Establish secure and responsible AI practices across governance, permissions, auditability, model/tool selection, data handling, context management, and cost optimization.
• Define metrics and dashboards to track AI adoption, productivity gains, workflow efficiency, quality improvements, security compliance, and business impact.
• Serve as a technical thought leader, mentor, and executive-facing advisor who raises AI fluency and communicates strategy, progress, risks, and impact clearly.

Impact

• Accelerate CPSG’s transition from AI-assisted development to AI-native and agentic engineering workflows.
• Deliver measurable improvements in productivity, quality, release confidence, security posture, and development cycle time.
• Create reusable AI assets, workflow patterns, and governance models that scale across teams and product lines.
• Act as a technical multiplier who shapes the long-term evolution of AI-enabled embedded and software engineering across the organization.

Minimum Qualifications:

• Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 8+ years of Software Engineering or related work experience.
OR
Master's degree in Engineering, Information Systems, Computer Science, or related field and 7+ years of Software Engineering or related work experience.
OR
PhD in Engineering, Information Systems, Computer Science, or related field and 6+ years of Software Engineering or related work experience.

• 4+ years of work experience with Programming Language such as C, C++, Java, Python, etc.

Required Qualifications

• Demonstrated Principal-level technical leadership, cross-team influence, architecture ownership, and organization-scale impact.
• Deep expertise in Generative AI, AI/ML fundamentals, LLM-based systems, model/tool selection, evaluation, optimization, and practical application in engineering environments.
• Hands-on experience building, deploying, or integrating GenAI solutions such as agentic workflows, RAG/context-aware systems, developer tools, automation frameworks, or AI-enabled engineering platforms.
• Proven ability to lead large-scale technical transformation across teams, influence without authority, shape architecture, and drive adoption in complex engineering organizations.
• Strong understanding of the SDLC, including requirements, design, implementation, code review, testing, CI/CD, release readiness, security workflows, and productivity measurement.

• Strong foundation in secure software development, responsible AI usage, data protection, governance, observability, and risk management for enterprise AI systems.
• Experience in systems software, embedded software, platform software, or…