
Job Overview
Location
Gurugram
Job Type
Full-time
Category
Software Engineering
Date Posted
March 26, 2026
Full Job Description
đź“‹ Description
- • SDET II (Night Shift) at Netomi AI Inc. is a critical role focused on ensuring the quality, reliability, and performance of the company’s agentic AI platform used by global enterprises such as Delta Airlines, MetLife, and United Airlines. This position directly contributes to delivering seamless, scalable, and secure AI-driven customer experience solutions that drive operational efficiency and customer satisfaction for Fortune 500 clients.
- • The role involves validating complex AI-powered systems through rigorous testing strategies, safeguarding product integrity in a fast-paced, innovation-driven environment where quality directly impacts enterprise trust and adoption.
- • Day-to-day responsibilities include designing, developing, and executing automated test frameworks for web, API, and mobile applications using tools like Selenium, Cypress, or Playwright, with a focus on regression, smoke, and performance testing.
- • Collaborate closely with software engineers, product managers, and DevOps teams in an Agile/Scrum environment to understand feature requirements, define test criteria, and integrate testing into CI/CD pipelines using Jenkins, GitLab CI, or similar tools.
- • Develop and maintain comprehensive test plans, test cases, and test scripts that cover functional, non-functional, and edge-case scenarios, ensuring high test coverage and early defect detection.
- • Perform API testing using Postman, REST Assured, or similar tools to validate data integrity, authentication, rate limiting, and response correctness across microservices.
- • Conduct performance and load testing using JMeter or k6 to assess system behavior under peak loads, identifying bottlenecks and recommending optimizations for scalability.
- • Participate in root cause analysis of production defects, contribute to blameless postmortems, and drive continuous improvement in testing processes and quality gates.
- • Mentor junior SDETs and QA engineers by sharing best practices in test automation, coding standards, and quality advocacy, fostering a culture of ownership and excellence.
- • Stay current with emerging trends in AI/ML testing, including model validation, drift detection, and fairness assessment, to ensure the reliability of AI agents in production.
- • About the team or company: Netomi AI Inc. is a Y Combinator-backed, venture-funded leader in agentic AI for enterprise CX, trusted by global brands to automate customer interactions at scale with measurable ROI in cost reduction and satisfaction improvement.
- • The engineering team operates with a high degree of autonomy, innovation, and technical rigor, emphasizing clean code, automation-first mindsets, and data-driven decision-making in a collaborative, flat-hierarchy culture.
- • What the person can learn or achieve in this role: Gain deep expertise in testing AI-driven systems at enterprise scale, including validating natural language understanding, dialogue flows, and integration with CRM/ERP systems—skills highly sought after in the evolving AI quality assurance landscape.
- • Opportunity to influence quality strategy for a rapidly growing AI platform, work with cutting-edge technologies, and contribute to products used by millions of end-users globally, positioning you as a specialist in AI systems testing and quality engineering.
Skills & Technologies
About Netomi AI Inc.
Netomi AI Inc. provides conversational AI software that automates customer support across email, chat, messaging, and voice channels. The platform integrates with CRM, e-commerce, and contact-center systems to resolve tickets, predict intent, and escalate complex issues to human agents. Founded in 2015, the company serves retail, telecom, financial services, and travel brands, measuring outcomes through containment rate, response time, and CSAT improvements. Headquartered in San Francisco with development offices globally, Netomi focuses on multilingual natural language understanding, reinforcement learning, and secure enterprise deployment.
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