AI Software Development Engineer in Test

placeTijucas calendar_month04/05/2025

AI Software Development Engineer in Test - We are seeking a highly skilled AI Engineer to join our Software Quality Engineering (SQE) team.
The ideal candidate will have a dual focus: contributing to AI/ML solution development while performing responsibilities typical of a Software Development Engineer in Test (SDET).
This role involves building and deploying AI-powered solutions for enhancing software testing, automation frameworks, and processes.

Responsibilities: AI Engineering: 1.

AI Solution Development: 1.

Develop AI-powered solutions to improve software quality assurance processes.

Leverage frameworks like Retrieval-Augmented Generation (RAG) and other state-of-the-art AI/ML frameworks to design innovative testing and debugging tools.

Create models for triaging and debugging test case failures using structured and unstructured data, such as log files.

Framework Optimization: 2.

Enhance testing processes with AI to automate root-cause analysis, bug detection, and recommendation systems.

Collaborate with cross-functional teams to integrate AI solutions into existing software testing pipelines.

MLOps Development: 3.

Design, implement, and maintain robust MLOps pipelines for continuous integration and deployment of AI/ML models.

Automate workflows for model training, evaluation, and deployment.

SDET Responsibilities: 1.

Test Case Creation & Maintenance: 1.

Write, maintain, and optimize manual and automated test cases for functional, regression, and performance testing.

Collaborate with development teams to define test strategies and acceptance criteria for new features.

Automation Framework Development: 2.

Build and enhance automation frameworks for Android, Web, and backend systems using tools like Appium, Selenium, or equivalent.

Integrate automation pre-checks, post-checks, and reporting systems to ensure test case reliability.

Code Review & Collaboration: 3.

Review and provide feedback on code quality and design for testability.

Work closely with software engineers and other SDETs to drive testing best practices.

Test Data Management: 4.

Work with engineering teams to ensure proper test data management, including synthetic data generation for testing AI-based solutions.

Mandatory Skills Description: AI/ML Expertise: - Strong knowledge of machine learning frameworks (e.
g.
, TensorFlow, PyTorch, Scikit-learn).

Experience with MLOps tools (e.

g.
, MLflow, Kubeflow, AWS Bedrock, SageMaker).

Proficiency in RAG frameworks and understanding of knowledge-based systems.
Familiarity with LangChain and Hugging Face Transformers.

Experience working with Streamlit.

Strong command on all AWS services and prompt engineering techniques and Dspy.

SDET Expertise: - Proficiency in test automation tools (e.
g.
, Appium, Selenium, JUnit, TestNG).

Strong programming skills in languages like Python, Java.
Experience with CI/CD tools like Jenkins, GitLab CI, or equivalent.

General Skills: - Familiarity with cloud platforms (e.
g.
, AWS, GCP, Azure).

Knowledge of SQL and database management for test data validation.
Strong debugging and troubleshooting skills in software systems.

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