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 up-to-date 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

📌 Manager, Software Quality Assurance (Pune)
🏢 Wolters Kluwer India Private
📍 Pune