Software Development Engineer in Test (SDET II)

 Software Development Engineer in Test (SDET II) with experience testing AI-powered applications, Generative AI solutions, and Agentic AI systems. This role is responsible for designing and executing quality engineering activities, developing automation solutions, validating APIs and integrations, supporting CI/CD and release readiness, and promoting a quality-first engineering mindset across traditional and AI-driven platforms.

Key Experience Requirements

•            8+ years of software quality engineering, test automation, or SDET experience in Agile development environments.

•            Strong proficiency in Python, Pytest, Pandas, Dataframes and object-oriented programming principles.

•            6+ years of experience with UI automation frameworks such as Playwright or Selenium.

•            6+ years of experience testing RESTful APIs and microservices.

•            Hands-on experience with CI/CD pipelines and DevOps practices.

•            Experience working with SQL and NoSQL databases.

•            Experience with AWS or other cloud-based platforms.

•            Understanding prompt engineering, prompt validation, hallucination detection, bias testing, guardrail validation, and AI output evaluation.

•            Knowledge of LLMs, Retrieval-Augmented Generation (RAG), AI agents, MCP, and AI-assisted workflows.

•            Ability to develop QA strategies, test frameworks, and automation solutions for AI-driven applications.

•            Analytical, problem-solving mindset with continuous learning and quality-first engineering habits.

Key Responsibilities

•            Design and execute functional, integration, system, regression, and automation testing activities.

•            Apply Shift-Left testing practices by participating in requirement reviews and defining test scenarios early in the SDLC.

•            Build, maintain, and enhance UI automation frameworks using Python, PyTest, and Playwright.

•            Perform manual and automated API testing using industry-standard tools and frameworks.

•            Collaborate with developers, product owners, business analysts, and DevOps teams to ensure product quality.

•            Work with SQL and NoSQL databases for backend validation and data testing.

•            Support CI/CD pipelines and ensure automated tests are integrated into deployment processes.

•            Create test plans, test cases, test data strategies, and quality metrics dashboards.

•            Manage defect lifecycle activities and provide clear reporting of quality risks.

•            Develop AI test datasets, benchmarks, evaluation frameworks, and automated validation approaches.

•            Experience with performance and load testing using JMeter or similar tools.

•            Knowledge of AI observability, model monitoring, and evaluation platforms.

•            Experience with monitoring tools such as New Relic, Datadog, Splunk, or CloudWatch.

 

 Preferred Qualifications

•            Experience testing Generative AI and Agentic AI applications.

•            Ability to validate AI outputs for accuracy, reliability, and business relevance.

•            Knowledge of AI agent workflows, prompt testing, hallucination detection, and model evaluation.

•            Understanding AI safety, guardrails, security, compliance, and responsible AI practices.

•            Experience with LangChain, LangGraph, MCP, OpenAI, Anthropic, Azure OpenAI, Kiro or Amazon Bedrock.

•            Familiarity with AI governance, risk management, and AI quality metrics.