Firmware QA Manager

Firmware QA Manager

We are seeking a Firmware Quality Assurance (QA) Manager to build, lead, and scale an AI-first firmware quality assurance team within our Firmware Engineering department. This is not a role where AI is a nice-to-have; it is foundational to how we expect this team to operate. You will establish QA strategy, processes, and tooling that treat AI as a core capability, not an afterthought, leveraging large language models, AI-assisted code review, intelligent test generation, and automated analysis across our full smart water product portfolio. That portfolio includes MACH 10 ultrasonic meters for residential, commercial, and industrial applications; the R900 System of RF and cellular meter interface units (MIUs) supporting AMR and AMI deployments; R900 Gateway fixed network data collectors; and mobile data collection solutions. The ideal candidate is someone who is already using AI tools daily in their engineering workflows, has strong opinions about where AI accelerates quality outcomes, and is excited to build a team culture where AI fluency is a baseline expectation.

Our firmware engineering organization is committed to leading AI adoption, not just experimenting with it. For this role, that means:

• AI is embedded in the workflow, not bolted on. You'll integrate AI tools like Claude, Claude Code, CodeRabbit, Qodo, and emerging AI-powered testing platforms directly into day-to-day QA operations, from test case generation and code review to defect triage and root cause analysis.
• You'll hire and develop AI-fluent engineers. When building your team, AI proficiency is a core competency, not a bonus. You'll set expectations that every QA engineer on your team actively uses AI tools to multiply their effectiveness.
• You'll measure AI's impact. You'll establish metrics to quantify how AI tooling improves test coverage, defect detection rates, time-to-release, and overall team throughput, and you'll use that data to drive continuous improvement.
• You'll push boundaries. You'll continuously evaluate emerging AI capabilities and advocate for their adoption where they can meaningfully improve firmware quality, from AI-generated test harnesses to LLM-assisted specification analysis and anomaly detection in field data.

Key Responsibilities

AI-Driven QA Strategy & Process

• Define and own the firmware QA strategy across the full product portfolio.
• Architect QA workflows that leverage AI for test case generation, automated code review, regression analysis, and intelligent defect prioritization.
• Establish and continuously improve QA processes, testing frameworks, and quality metrics aligned with the firmware development lifecycle.
• Develop and maintain comprehensive test plans, test cases, and traceability matrices that map to product requirements, using AI to accelerate creation and maintenance.
• Champion a quality-first culture within the firmware organization, integrating QA earlier into the development process (shift-left testing) with AI-powered feedback loops.
• Lead post-mortem and root cause analysis efforts for field escapes and quality issues, leveraging AI-assisted analysis to drive corrective and preventive actions faster. Team Leadership — Building an AI-First Team
• Build, mentor, and manage a team of firmware QA engineers where AI fluency is a core hiring criterion and performance expectation.
• Foster a team culture of experimentation and continuous learning with AI tools and encourage engineers to find new ways AI can improve their work.
• Establish clear performance expectations that include effective AI tool utilization, conduct regular 1:1s, and deliver meaningful performance reviews.
• Track and report on AI adoption metrics within the QA team, including usage rates, productivity gains, and quality improvements attributable to AI tooling.
• Collaborate with firmware development leads to align QA priorities with project schedules and release milestones.

Technical Execution

• Oversee the design and execution of test strategies for embedded firmware, including functional testing, regression testing, integration testing, stress testing, and field simulation.
• Drive AI-assisted test automation by using LLMs and AI tools such as Qodo to generate test scripts, review test coverage gaps, and analyze test results at scale.
• Establish and maintain firmware unit testing practices using frameworks such as CppUTest, ensuring consistent coverage across product lines.
• Implement and enforce static analysis standards using tools such as PC-lint Plus to catch defects, memory issues, and coding standard violations early in the development cycle.
• Ensure thorough validation of wireless communication protocols including LoRaWAN, cellular (LTE-M/NB-IoT), and proprietary RF protocols.
• Drive development and expansion of automated test infrastructure, including hardware-in-the-loop (HIL) test systems and CI/CD-integrated test pipelines.
• Validate firmware update mechanisms, bootloader integrity, and rollback scenarios across all product lines.
• Leverage RTOS runtime analysis and trace visualization tools such as Percepio Tracealyzer to diagnose timing, scheduling, and performance issues in firmware.
• Partner with Systems Engineering to validate end-to-end system behavior, interoperability, and compliance with regulatory requirements.

Cross-Functional Collaboration

• Work closely with Product Management to understand customer requirements and translate them into testable acceptance criteria.
• Coordinate with field engineering and technical support teams to triage field-reported issues and prioritize regression testing.
• Collaborate with Security and Compliance teams to ensure firmware meets cybersecurity standards and penetration testing requirements.
• Interface with third-party vendors and tool providers to optimize QA workflows.
• Serve as an AI adoption champion within the broader engineering organization, sharing learnings and best practices across teams.

Required Qualifications

• Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field.
• 7+ years of experience in firmware/embedded software quality assurance or testing.
• 3+ years of experience managing or leading QA teams.
• Demonstrated, hands-on experience using AI/LLM tools (e.g., Claude, ChatGPT, Copilot, Claude Code, Cursor, Codex, Qodo) in engineering workflows.
• Strong understanding of embedded systems architectures, microcontrollers, RTOS, and low-level firmware concepts.
• Hands-on experience with test automation for embedded systems (HIL, SIL, scripted test harnesses).
• Familiarity with wireless communication protocols (LoRaWAN, BLE, cellular IoT, RF systems).
• Experience with version control systems (Git/Bitbucket), CI/CD pipelines (TeamCity, Jenkins), and defect tracking tools (Jira).
• Experience with firmware unit testing frameworks (e.g., CppUTest, Unity) and static analysis tools (e.g., PC-lint Plus, Polyspace, Coverity).
• Solid understanding of software development lifecycles, Agile/Scrum methodologies, and requirements traceability.

Preferred Qualifications

• Master's degree in a relevant engineering discipline.
• Track record of measuring and reporting ROI on AI tool adoption within engineering teams.
• Experience with battery-powered, field-deployed IoT devices and the unique testing challenges they present (power profiling, long-duration soak testing, environmental testing).
• Familiarity with firmware debugging tools and crash analytics platforms.
• Experience with Python, C, or scripting languages for test automation development.
• Knowledge of water utility or AMI (Advanced Metering Infrastructure) industry.
• ISTQB or similar QA/testing certification.

Travel: Up to 10%

Location: Duluth, Georgia or Tallassee, Alabama