Senior Software Engineer In Test

Overview

Senior Software Development Engineer in Test (SDET) role focused on test automation, data validation and AI-assisted quality engineering for data-intensive healthcare marketing applications.

What you'll do

• Design, develop, and maintain scalable test automation frameworks for UI, API, database, and end-to-end testing.
• Develop and execute automated tests using Python Pytest, Playwright, Robot Framework or equivalent technologies.
• Define test strategies, improve automation coverage, and integrate automated tests into CI/CD pipelines.
• Perform functional, integration, regression, and data validation testing across complex applications and distributed systems.
• Understand data as a product, including data flows, transformations, upstream and downstream dependencies, quality requirements, and business impact.
• Analyze end-to-end business requirements, translate them into effective test scenarios, and identify functional dependencies, edge cases, and potential risks.
• Investigate test failures, analyze application logs, identify root causes, and collaborate with engineering teams to resolve defects.
• Leverage AI-assisted engineering tools for requirement analysis, test design, automation development, debugging, and test maintenance.
• Independently identify opportunities to apply AI/GenAI in quality engineering, develop effective prompts, and validate AI-generated solutions for accuracy, reliability, and maintainability.
• Contribute to continuous improvements in test automation, engineering productivity, product reliability, and quality processes.
• Collaborate with developers, product managers, data engineers, and other stakeholders to ensure end-to-end product quality.
• Communicate technical approaches, validation results, quality risks, and recommendations clearly and effectively.

What you'll need

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related technical discipline, or equivalent practical experience.
• 3.5+ years of professional experience in software testing, test automation, or SDET roles.
• Strong programming and problem-solving skills, preferably in Python.
• Hands-on experience designing, developing, and maintaining test automation frameworks using Pytest, Playwright, Robot Framework, or similar tools.
• Strong understanding of software testing methodologies, test design techniques, and automation best practices.
• Experience with UI testing and Automation, GraphQL, REST API testing, database testing, and end-to-end application validation.
• Working knowledge of Git, Jenkins, CI/CD pipelines, and agile software development practices.
• Strong SQL skills with experience validating complex datasets, transformations, and data integrity.
• Understanding of data pipelines, data dependencies, and data quality principles.
• Ability to analyze business requirements, understand end-to-end workflows, and translate them into comprehensive validation scenarios.
• Strong analytical reasoning, debugging, and root-cause analysis skills.
• Practical experience using AI coding assistants such as Cursor, Claude, ChatGPT, GitHub Copilot, or equivalent tools for development, testing, and troubleshooting.
• Ability to formulate effective prompts with appropriate technical and business context, evaluate AI-generated outputs, and apply them to engineering tasks.
• Ability to independently identify practical AI/GenAI use cases to improve automation effectiveness, test coverage, and engineering productivity.
• Foundational understanding of Generative AI, Large Language Models (LLMs), and their applications in software engineering.
• Strong written and verbal communication skills, with the ability to clearly articulate technical reasoning, findings, and recommendations.
• Ability to work collaboratively across engineering and product teams, demonstrate ownership, and independently drive assigned responsibilities.

Nice to have

• Experience with ClickHouse, Apache Spark, BigQuery, MySQL, or similar data processing and analytical platforms.
• Experience in testing data pipelines, distributed systems, or large-scale data-intensive applications.
• Familiarity with Docker, Kubernetes, cloud environments, and application observability.
• Experience with performance testing tools such as JMeter or equivalent solutions.
• Knowledge of AI/LLM applications, Retrieval-Augmented Generation (RAG), LangChain, LangGraph, or similar agentic AI frameworks.
• Familiarity with Model Context Protocol (MCP) and tool/function calling.
• Exposure to AI evaluation and observability tools.
• Understanding of LLM evaluation concepts, including response accuracy, relevance, hallucination detection, tool-selection accuracy, and agent task completion.
• Familiarity with AI security testing, prompt injection, sensitive data protection, and AI application performance monitoring.
• Experience working with healthcare technology, advertising technology, or data-intensive enterprise applications.

Details

• Location: Pune, India.
• Hybrid-friendly culture with flexible work options for the India-based team.