Quality Assurance Manager

Role Summary

The Quality Manager AI & Automotive Software is responsible for defining, implementing,

and governing quality standards across automotive embedded middleware products,

processes, and AI-enabled solutions. This role ensures compliance with automotive, safety,

cybersecurity, and AI governance standards while driving continuous improvement,

operational excellence, responsible AI usage, and customer satisfaction.

Key Responsibilities

Quality Management System (QMS)

- Develop, implement, and maintain a robust QMS aligned with ISO 9001 / IATF 16949 and

ASPICE standards.

- Ensure compliance with industry best practices, customer requirements, and regulatory

standards.

AI & Advanced Quality Engineering

- Govern quality assurance for AI-enabled solutions, including data quality, model

validation, bias detection, explainability, and performance monitoring.

- Use AI tools for automated reviews, defect prediction, documentation validation,

compliance checks, and risk prediction.

- Apply AI-driven methods for requirements analysis, code quality evaluation, test

optimization, and process analytics.

- Drive process improvement initiatives using AI, automation, and data-driven insights.

- Promote responsible AI usage, AI ethics, and risk management across teams.

Automotive Standards & Compliance

- Ensure adherence to AUTOSAR, ISO 26262 (Functional Safety up to ASIL-D), ISO/SAE

21434 (Cybersecurity), and ASPICE.

- Lead and support internal and external audits, assessments, and certification activities.

Risk Management & Quality Assurance

- Establish and maintain a comprehensive risk management framework covering functional

safety, cybersecurity, compliance, and AI-related risks.

- Define quality metrics, KPIs, and objectives to monitor and improve product quality

throughout the SDLC.

Supplier & Stakeholder Management

- Manage supplier quality, including assessments, audits, and compliance validation.

- Collaborate with cross-functional teams, customers, suppliers, and certification bodies.

Training & Leadership

- Coach and mentor teams on quality management best practices, AI usage, safety, and

cybersecurity standards.

- Foster a strong culture of quality, innovation, and continuous improvement.

Qualifications

- Bachelors degree in Engineering, Computer Science, or a related field advanced degree

preferred.

- Extensive experience in quality management within the automotive or embedded software

domain.

- Strong understanding of SDLC methodologies, quality assurance, and risk management

principles.

AI Competency (Mandatory)

- Hands-on experience with AI tools such as Copilot, LLMs, AI-based static analysis,

automated quality checks, and risk prediction systems.

- Exposure to AI/ML systems or data-driven solutions in engineering or quality contexts.

Certifications (Mandatory / Preferred)

- Automotive SPICE (ASPICE): Provisional / Competent / Lead Assessor.

- ISO 9001 / IATF 16949 Lead Auditor or Internal Auditor.

- Certified Quality Manager (CQM, CMQ/OE) or equivalent.

Key Competencies

- Automotive software quality expertise

- AI risk management and ethical awareness

- Strong analytical and problem-solving skills

- Excellent leadership, communication, and stakeholder management skills