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WHAT YOU’LL DO
Create and sustain GenAI digital assistants using LLMs and RAG.
Work with data scientists, software architects, and engineers to design and implement digital assistant functionalities.
Focus on scalability, reliability, and performance of digital assistant applications.
Implement automated deployment and monitoring processes for digital assistants using CI/CD tools, preferably Jenkins.
Enhance digital assistant workflows to improve efficiency and user experience, utilizing Handlebars and SpEL for dynamic content rendering and prompt engineering techniques for better responses.
Keep abreast of the latest developments in AI, LLMs, and software development.
Integrate digital assistants with cloud platforms.
Work with data platforms such as Databricks, ADLS, and Apache Spark for efficient data management and processing.
Use YAML for effective configuration management of digital assistant applications.
WHAT YOU’LL BRING
Master’s degree in computer science, data science, engineering, or a related field.
Strong proficiency in Python and extensive experience in software engineering.
Expertise with CI/CD tools, preferably Jenkins.
Experience in cloud development, with a preference for SAP Business Technology Platform (BTP).
Experience with Databricks and Azure Data Lake Storage (ADLS).
Familiarity with Apache Spark for large-scale data processing.
Skills in Handlebars and Spring Expression Language (SpEL).
Experience in prompt engineering with large language models (LLMs).
Strong understanding of AI and machine learning concepts, with proficiency in YAML for configuration management.
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