QE AI Engineer, NTT DATA

• Relevant experience in software engineering, SDET, Quality Engineering, or test automation roles
• Strong hands-on experience developing and maintaining automated test solutions
• Experience contributing to software delivery across the full SDLC, not limited to test execution
• Experience working with at least one modern programming language such as Python (is a MUST), Java, JavaScript/Typescript or C#
• Experience with web, API, and non-functional testing approaches
• Experience using CI/CD pipelines to integrate and run automated tests
• Good understanding of object-oriented programming principles and modern engineering practices
• Experience working with Git-based source control and collaborative development workflows
• Strong problem-solving and analytical skills
• Good written and verbal communication skills
• Ability to work independently under general direction and collaborate effectively as part of a team
• We are looking for someone with practical experience or strong exposure to AI-enabled engineering solutions, ideally in testing, automation, or developer productivity use cases
• This may include experience with:
• AI application patterns
• Retrieval-Augmentation Generation (RAG)
• Prompt engineering
• Tool calling
• Agentic workflows
• Evaluation of LLM-based outputs
• Frameworks and orchestration
• LangChain
• LangGraph
• CrewAI
• Models and platforms
• OpenAI and/or Azure OpenAI
• Vector search and retrieval
• Weaviate or equivalent vector database technology
• Data and model support
• Selecting and preparing data for AI-enabled solutions
• Evaluating model or workflow outputs
• Identifying opportunities to improve data quality and model effectiveness
• Typical QE use cases
• Test generation
• Defect analysis
• Quality reporting
• Knowledge retrieval
• Engineering support tooling
• Experience with fine-tuning LLMs is beneficial but not required

Desirable

• As a QE AI Engineer, you will join a Quality Engineering team focused on modern software delivery, automation, and AI-enabled engineering across the SDLC
• This is a hands-on engineering role for someone with strong software development and Quality Engineering experience who can contribute to the design, build, and improvement of modern QE solutions
• You will work across test automation, engineering quality, and AI-enabled accelerators that support delivery teams in improving quality, speed, and efficiency
• You will help develop reusable QE assets, frameworks, and tooling, while working closely with engineers, testers, and stakeholders to embed quality earlier in the lifecycle
• You will also support the adoption of AI/GenAI capabilities in practical QE use cases such as test generation, defect analysis, and quality reporting
• Design, build, test, and maintain quality engineering solutions across the SDLC
• Contribute to the development and enhancement of reusable QE assets, accelerators, and automation frameworks
• Apply a shift-left approach by helping teams embed quality practices earlier in the development lifecycle
• Build and support automation across web, API, and non-functional testing
• Contribute to AI-enabled QE use cases such as:
• Test case generation
• Test data preparation and augmentation
• Defect analysis
• Quality metrics and reporting
• Engineering productivity tooling
• Work with structured and unstructured data to support AI and quality engineering solutions
• Evaluate the effectiveness of automation and AI-enabled solutions, and recommend practical improvements
• Monitor and report on progress, identify issues, and help resolve delivery and engineering challenges
• Collaborate with developers, product teams, and other engineers to understand requirements and deliver fit-for-purpose solutions
• Participate in reviews of code, design, and test solutions
• Support and mentor team members where appropriate, including sharing knowledge of modern QE and AI-assisted engineering practices