Product quality Head

Role & responsibilities

Ideal Candidate Profile

• A seasoned QA professional with

  strong experience in embedded hardware + software products

  .
• Proven ability to operate in

  fast-paced, mid-sized organizations

  with dynamic leadership and high execution ownership.

• Assertive, self-driven, and process-oriented

  leader who can inspire and mentor cross-functional teams.
• Thrives under pressure and demonstrates

  exceptional problem-solving and analytical skills

  .
• Hands-on with modern QA practices, tools, and metrics.
  

Educational Qualification

• Diploma + Engineering (Circuit Branch)

  or

  B.E. (Electronics / EEE / ECE / Instrumentation / related circuit branch)

Experience Range

• 15 to 17 years

  (for fast-track professionals)

• 18 to 19 years

  (for standard career progression profiles)

Preferred Background

• Experience in

  fast-paced, mid-sized growth organizations

  (preferred over large structured MNC setups).
• Exposure to

  high-performance leaders

  who drive results through rigorous expectations and stretch goals.
• Experience in

  vibrant B2C or product-based environments

  with customer exposure and accountability.

Who Will Not Fit

• Professionals from

  highly structured MNC environments

  with limited exposure to ambiguity, multitasking, or cross-functional agility.
• Candidates expecting rigidly layered teams or policy-heavy organizations.
  

Key Responsibilities

• Leadership & Strategy

• Lead and develop the Product Quality team spanning hardware, firmware, and software testing.
  
• Define and execute the

  quality strategy, roadmap, KPIs, and scorecards

  across all product lines.
• Partner with R&D, Manufacturing, Reliability, and Customer Service teams to drive continuous improvement.
  

• Process & Standards

• Establish and enforce

  robust quality processes

  aligned with global standards.
• Drive

  CAPA, FMEA, and RCA frameworks

  to enhance product reliability and field performance.
• Extend quality frameworks for

  custom product variants and NRE programs

  .

• Customer & Data Insights

• Review customer tickets and failure data; ensure

  timely root-cause analysis

  and corrective actions.
• Utilize feedback and field data to

  enhance product quality and design robustness

  .

• Automation & Tools

• Implement test automation using

  Python, OpenCV, and GStreamer

  for image and functional testing.
• Define

  quantitative image quality metrics

  and build standard testing protocols.
• Introduce

  QA dashboards

  and data analytics for real-time visibility into KPIs and trends.

• Reporting & Governance

• Ensure

  speed, accuracy, and completeness

  of all quality documentation and reports.
• Report quality metrics, trends, and improvement initiatives to management on a periodic basis

Thanks & Regards

Dharani S