Senior QA Engineer Manual and Automation
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.
You will design and build scalable data pipelines for AI workflows. You will integrate and operationalize LLMs and multimodal models, evaluate and optimize their performance, and develop Java and Python backend services. You will 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
- Java proficiency
- Python proficiency
- Cloud environment experience with AWS, GCP, or Azure
- Kafka experience
- SQL knowledge
- NoSQL database knowledge
- Machine learning fundamentals
- Natural language processing knowledge
- Information retrieval knowledge
- RAG architecture familiarity
- Data pipeline experience for training, evaluation, or experimentation
- Prompt optimization, model evaluation, and cost-aware experimentation experience