Lead Software Development Engineer in Test - AI

New

JobgetherAI software

Fully remote working arrangement within India.Full-TimeLead

Salary not disclosed

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Job Details

Experience: At least 7 years of professional experience in Quality Assurance (QA), Software Development Engineering in Test (SDET), or related software testing roles.
Required Skills: AWSGCPMicrosoft AzureCI/CDQuality AssuranceMLOps

At least 7 years of professional experience in QA, SDET, or related software testing roles.
Deep expertise in AI tools and model testing, including testing strategies for complex AI-powered applications.
Strong understanding of RAG, hallucination detection, model drift, bias evaluation, and model reliability.
Experience architecting and implementing large-scale, reusable, cross-platform test automation frameworks.
Experience defining and managing end-to-end quality strategies at the product or organizational level.
Technical leadership experience mentoring engineers, developing team expertise, and establishing best practices.
Ability to influence cross-functional stakeholders and contribute to technical and architectural discussions.
Ability to make independent decisions about testing strategies, tools, frameworks, and AI quality methodologies.
Strong problem-solving and analytical skills.
Experience with CI/CD pipelines and cloud platforms such as AWS, GCP, or Microsoft Azure is an advantage.
Familiarity with MLOps pipelines and monitoring systems for AI-powered applications is a plus.
Exposure to performance, load, and scalability testing of AI workloads is desirable.

Define and lead the QA strategy for AI products and engineering initiatives.
Architect, develop, and implement large-scale, reusable, cross-platform test automation frameworks.
Own the AI vertical's end-to-end quality charter across product reliability, scalability, consistency, and performance.
Design testing strategies for AI systems, including RAG, hallucinations, model drift, and bias.
Evaluate AI model behavior, accuracy, reliability, and consistency across scenarios and operating conditions.
Set testing methodologies and engineering standards, and drive organization-wide quality initiatives.
Shape the AI quality roadmap and address technical risks affecting product reliability and scalability.
Collaborate with Software Engineering, Product, and Architecture teams and contribute to architectural discussions.
Lead, coach, and mentor the QA/SDET team and promote knowledge sharing and continuous improvement.
Monitor quality metrics, identify systemic risks, and implement improvement initiatives.

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