Senior QA Engineer Manual and Automation
Posted Updated 13
views
Summary
Build and optimize AI data pipelines, integrate LLMs and multimodal models, and develop Java/Python backend services to turn AI capabilities into user features.
Design and build scalable data pipelines for AI workflows, operationalize LLMs and multimodal models, evaluate and optimize their performance, and develop Java and Python backend services. Implement RAG and information-retrieval pipelines, improve outputs through prompt engineering and A/B testing, and turn AI capabilities into end-user features.
Responsibilities
- Design and build scalable data pipelines for AI workflows
- Integrate and operationalize LLMs and multimodal models
- Conduct error analysis, model evaluation, and cost and performance optimization
- Develop and maintain Java and Python backend services
- Implement retrieval-augmented generation and information-retrieval pipelines
- Apply prompt engineering, validation, and A/B testing
- Collaborate with product and engineering teams to turn AI capabilities into end-user features
- Stay current with emerging AI trends and tools
Requirements
- 7+ years of hands-on software engineering experience
- B.Sc. in Computer Science or Software Engineering; M.Sc. is a plus
- Strong proficiency in Java and Python
- Experience in cloud environments such as AWS, GCP, or Azure
- Hands-on experience with Kafka, SQL, and NoSQL databases
- Familiarity with machine learning fundamentals, NLP, information retrieval, and RAG architectures
- Experience building data pipelines for training, evaluation, or experimentation
- Experience with prompt optimization, model evaluation, and cost-aware experimentation
- Self-driven mindset and curiosity to explore new tools, frameworks, and approaches in applied AI
