Wireless Software Engineer

About the role

Qualcomm Technologies, Inc. is seeking a Modem Software Engineer to join the Modem Systems Software team. This role is part of a team that builds the low-level firmware and protocol software powering cellular connectivity across billions of devices worldwide.

Responsibilities

• Design, implement, and optimize real-time embedded modem software across protocol layers, drivers, and platform services, meeting strict latency, memory, and power constraints.
• Apply rigorous data-structure and algorithm design to build efficient, scalable firmware components.
• Own end-to-end feature delivery: requirements, architecture, implementation, unit/integration testing, on-target bring-up, and maintenance.
• Pioneer AI-native development practices within the team — integrate AI coding agents into daily workflows, establish agent rules and prompt patterns, and measurably reduce development and debug cycle time.
• Build and maintain AI-assisted tooling for code review, static analysis, test synthesis, and automated crash/log triage over the modem codebase.
• Debug and root-cause complex, multi-layer issues on target hardware, increasingly leveraging AI-assisted analysis of logs, traces, and RAM dumps.
• Collaborate cross-functionally with systems, hardware, test, and integration teams to deliver production-quality modem firmware.
• Contribute to code reviews, design reviews, and continuous improvement of engineering standards — including standards for the responsible and effective use of AI in the SDLC.
• Mentor peers on both embedded fundamentals and AI-native engineering techniques.

Requirements

• Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field.
• Core Embedded & Systems Engineering.
• Strong command of data structures and algorithms with the ability to reason about time/space complexity in memory- and cycle-constrained environments.
• Deep understanding of operating systems concepts: scheduling, concurrency, interrupts, memory management, IPC, real-time constraints, and RTOS internals (e.g., QuRT, ThreadX, FreeRTOS, or similar).
• Proven programming proficiency in modern C/C++ (C++17 and beyond), including performance optimization, cache-aware design, and lock-free/thread-safe patterns.
• Familiarity with embedded software on DSP and Arm architectures, including familiarity with SIMD/vectorization, DMA, and low-power design.
• Experience with debugging on target hardware — JTAG, logic analyzers, protocol analyzers, crash-dump / RAM-dump analysis, and log parsing.
• Familiarity with device drivers, HAL layers, boot flows, and hardware/software co-design.
• AI-Native Engineering: AI-first mindset; treat AI tooling as a core engineering multiplier, not an afterthought.
• Experience using AI coding assistants and agentic tools (e.g., GitHub Copilot, Cline, Claude/GPT-based agents) to generate, refactor, and review embedded C/C++ at scale.
• Ability to build and maintain AI-augmented developer workflows: prompt libraries, agent rules, retrieval-augmented context over large firmware codebases, and MCP-style tool integrations.
• Experience applying LLMs to crash triage, log summarization, root-cause analysis, and automated defect classification in complex embedded systems.
• Comfort evaluating AI output critically: understanding hallucination risks, validating generated code against timing/memory budgets, and enforcing safety and correctness in real-time firmware.

Qualifications

• Minimum Qualifications: Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field.
• Preferred Qualifications: Core Embedded & Systems Engineering; strong command of data structures and algorithms; deep understanding of operating systems concepts; proven programming proficiency in modern C/C++; experience with embedded software on DSP and Arm architectures; experience with debugging on target hardware; familiarity with device drivers, HAL layers, boot flows, and hardware/software co-design; AI-native Engineering mindset; experience using AI coding assistants and agentic tools; ability to build and maintain AI-augmented developer workflows; experience applying LLMs to crash triage, log summarization, root-cause analysis, and automated defect classification; comfort evaluating AI output critically.

Skills

• Core Embedded & Systems Engineering
• Data Structures and Algorithms
• Operating Systems Concepts
• Modern C/C++ Programming
• Embedded Software Development
• AI Coding Assistants and Agentic Tools
• LLM Application in Embedded Systems
• Debugging on Target Hardware
• Device Drivers and HAL Layers
• Boot Flows and Hardware/Software Co-Design
• AI-Native Engineering Mindset
• Evaluating AI Output Critically

Benefits

• Annual Discretionary Bonus Program
• Opportunity for Annual RSU Grants (employees on sales-incentive plans are not eligible for our annual bonus)
• Competitive Benefits Package

Pay

$93,600.00 - $140,400.00