This role is responsible for developing and maintaining AI-driven solutions using large language models (LLMs), prompt engineering, and associated Python frameworks. The individual will contribute to feature enhancements, troubleshoot application issues, and support the integration of RESTful APIs and databases, ensuring the delivery of reliable and scalable GenAI applications.
Key Responsibilities
1. Develop and enhance GenAI features using Python and prompt engineering techniques, ensuring effective utilization of large language models for assigned tasks.
2. Integrate RESTful APIs with GenAI solutions to enable seamless communication between application components and external services.
3. Maintain and update data storage using MySQL and VectorDB, supporting productive retrieval and embedding of information for AI models.
4. Implement and test prompt engineering strategies to optimize LLM outputs for specific business requirements.
5.
Participate in code reviews and collaborate within the development team to resolve bugs and ensure adherence to coding standards using Flask, Django, or FastAPI.
6. Support day-to-day troubleshooting and ticket resolution by monitoring application performance and addressing client requests related to GenAI functionalities.
7. Document enhancement activities and technical changes in alignment with CMMi and client requirements for project deliverables.
Skill Requirements
1. Strong Understanding Of Genai Concepts, Prompt Engineering, And Llm Usage In Practical Development Tasks.
2. Experience With Python Programming For Ai Solution Development.
3. Good Proficiency In Integrating Restful Apis With Backend Systems.
4. Familiarity With Mysql, Vectordb, And Embedding Techniques For Managing And Retrieving Data.
5. Exposure To Frameworks Such As Flask, Django, Or Fastapi For Building Scalable Applications.
6. Basic Knowledge Of Pinecone, Azure Ai Search, And Postgresql Is Valuable For Supporti