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.

ORMaster's degree in Engineering, Information Systems, Computer Science, or related field and 7+ years of Software Engineering or related work experience.

ORPhD 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…