Manager, Software Quality Assurance

We are seeking an experienced Manager II (M2) Software Automation Engineer to lead the design, implementation, and adoption of next-generation Quality Engineering solutions powered by Agentic AI, intelligent automation, and modern software testing practices. This role combines deep technical expertise with leadership responsibilities to modernize testing strategies, drive AI-assisted automation, and mentor engineering teams in building scalable, resilient, and intelligent quality solutions.

The ideal candidate has extensive experience in automation frameworks, cloud-native applications, AI/LLM technologies, and software engineering while leading cross-functional teams in delivering high-quality enterprise software.

Key Responsibilities

Technical Leadership

• Lead the architecture, design, and implementation of enterprise automation frameworks using modern technologies.
• Drive adoption of Agentic AI solutions for autonomous test generation, maintenance, defect triage, root cause analysis, and release validation.
• Establish engineering standards, best practices, and governance for automation and AI-assisted testing.
• Design scalable CI/CD quality gates supporting continuous delivery.
• Develop and implement comprehensive test strategies.
• Lead framework modernization initiatives from legacy automation to AI-powered solutions.
• Oversee the execution of automated and manual testing and generate traceable reporting.
• Prepare and present quality reports to senior management
• Collaborate with cross-functional teams to improve product quality.
• Define and monitor quality metrics and key performance indicators.
• Conduct performance reviews and provide career development opportunities.

Agentic AI & Intelligent Automation

• Design and implement AI agents for:
  • Automated test case generation
  • Self-healing test automation
  • Intelligent regression selection
  • Failure analysis
  • Root cause identification
  • Requirement-to-test traceability
  • Defect summarization
  • Test data generation
  • Risk-based testing
• Integrate Large Language Models (LLMs) into automation workflows.
• Evaluate and implement Agentic AI platforms, MCP (Model Context Protocol), prompt engineering, and Retrieval-Augmented Generation (RAG).
• Optimize token usage, AI performance, governance, and cost management.

Automation Engineering

• Develop scalable automation solutions for:
  • UI
  • API
  • Integration
  • Performance
  • Database
  • End-to-End testing
• Build automation using:
  • Playwright/Selenium
  • Java/C#
  • REST Assured
  • API
  • Postman

Software Engineering

• Apply SOLID principles and clean architecture.
• Build cloud-native automation services and APIs.
• Develop reusable testing utilities and AI integrations.

Cloud & DevOps

• Integrate automation into CI/CD pipelines.
• Deploy automation services on:
  • Azure
  • AWS
• Monitor quality metrics using Grafana, ADO

Required Qualifications

Education

• Bachelor's degree in Computer Science, Software Engineering, or related field.
• Master's degree preferred.

Experience

• 8-12+ years of software engineering or Quality Engineering experience.
• 5+ years designing enterprise automation frameworks.
• 3+ years leading engineering teams or technical initiatives.
• Experience implementing AI-assisted software development or testing solutions.
• Experience working within Agile/Scrum environments.

Our Interview Practices