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Software Engineer - WLAN

Job in Santa Clara, Santa Clara County, California, 95053, USA
Listing for: Qualcomm
Full Time position
Listed on 2026-06-12
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Software Engineer
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below
Position: Staff Software Engineer - WLAN

Overview

Company
Qualcomm Atheros, Inc.

Job Area

Job Area Engineering Group, Engineering Group >
Software Engineering

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.

We are seeking a Staff Software Engineer to join the WLAN HAL-PHY firmware team. At this level, you are expected to bring deep, hands-on technical expertise across the full firmware development lifecycle — from architecture through lab bring-up and customer release. You will serve as a technical anchor on the team: setting design direction, driving silicon validation, and elevating the quality of firmware across next-generation WLAN chipsets.

The team has fully adopted AI-assisted development workflows — spanning Claude Code and Git Hub Copilot for firmware generation, MCP-based servers for register lookup and crash triage, and end-to-end AI agent pipelines that span requirements analysis through code review. Candidates should be comfortable using these tools daily and are expected to contribute to their evolution as the team s AI toolchain matures.

What

Success Looks Like
  • Hands-on technical depth:
    You write production-quality C/C++ firmware daily — this is not a coordination or review-only role.
  • Architectural ownership:
    You drive design decisions independently, evaluate trade-offs, and document them for long-term team knowledge.
  • Cross-functional influence:
    You collaborate as a peer with chip designers, RF engineers, and hardware board engineers — not just as a consumer of their work.
  • Mentorship and code quality:
    You actively raise the bar for junior and mid-level engineers through design reviews, pairing, and constructive feedback.
  • Problem ownership:
    You take complex, ambiguous debug problems from initial triage through root cause and verified fix, without needing direction at each step.
AI-First Engineering Culture

This team treats generative AI tools as force multipliers, not optional add-ons. Every engineer — from new hires to staff — is expected to use AI coding assistants, MCP-powered analysis tools, and LLM-based agent workflows as part of their daily development loop. That means generating firmware code with AI, reviewing AI-produced diffs with the same rigor applied to human-authored code, using AI agents to accelerate crash triage and root cause analysis, and contributing improvements to the team s AI toolchain.

Engineers who thrive here are not intimidated by AI-generated output and are not uncritical of it — they know how to direct it, validate it against hardware specs and architecture constraints, and push the quality bar higher over time.

What You ll Use
  • AI coding assistants — Claude Code, Git Hub Copilot, Cursor for firmware generation, diff review, and HAL-PHY register access iteration
  • MCP server tool chains — cscope MCP for symbol navigation, swi-hw-sw MCP for SWI contract verification, Smart Scope and Time Travel for crash dump triage and root cause attribution
  • LLMCommittee automated code review — AI-driven multi-model review pipeline for pre-submit quality gating
  • AI-assisted SDLC pipelines — req-analysis, sw-sdd, and code-gen agents spanning requirements through implementation
  • LLM-based crash triage and regression RCA — FACT-RCA knowledge base, AI-generated hypotheses cross-checked against memory dumps and log data
Responsibilities
  • Lead software architecture enhancements using established SW design patterns; re-architect existing firmware modules and design new ones from the ground up
  • Write, review, and own production-quality low-level firmware in a resource-constrained embedded environment (small memory footprint DSP/ARM processors)
  • Develop WLAN offload firmware running on dedicated co-processor cores, independent of the host processor
  • Diagnose and resolve complex WLAN and RF system performance issues; analyze power, spectrum, and waveform quality using RF test equipment and IQ capture data
  • Design, implement, unit test, and document features for next-generation WLAN platforms (802.11be and beyond)
  • Partner with chip designers, hardware board engineers, and RF…
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