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Job description:
Implement new gen AI techniques for question answering, information retrieval, etc. As these become available in future
Implement new data pipelines to process data from sources or formats which may be added in future
Implement new features to support user needs (in-line with innovation in the front-end)
Implement any additional logic necessary to support scaling to a larger number of users (e.G. Management of requests to LLM endpoints)
Monitor and manage traffic to external LLM endpoints (e.G. Openai) to ensure performance and availability is in line with expectations
Monitor effects of changes in LLM versions as/when these become available from model providers (and develop code to address or take advantage of these changes, including fine-tuning and serving custom models)
Monitor and evaluate output quality to ensure alignment with expectations
Requirements:
Advanced Python programming skills, including experience with typical libraries used for GenAI application development
Understanding of access management and control, and experience implementing these
Understanding of continuous integration and continuous deployment (CI/CD) pipelines
Proficient in integrating frontend and backend code
Proficiency in Git, command line and docker
Solid understanding of Kubernetes
Experience with SQL and NoSQL databases
Experience implementing data ingestion pipelines using one or more modern ETL compute and orchestration frameworks (e.g. Azure Data Factory, Apache Airflow)
Knowledgeable about engineering best practices (testing, reviews, and design documentation)
This application requires the candidate to present certain personal information including date of birth when requested.