What You’ll Do
- Experience in creating GenAI applications such as answering engines, extraction components, and content authoring.
- Strong knowledge in developing RAG-based pipelines using frameworks like LangChain & LlamaIndex.
- Good understanding of various LLMs like Azure OpenAI and proficiency in their effective utilization.
- Expertise in crafting and optimizing prompts using different strategies, including providing context and zero-shot techniques.
- Skilled in creating prompts that efficiently guide LLMs to generate outputs meeting business requirements.
- Solid working knowledge of the engineering components essential in a Gen AI application, including Vector DB, caching layer, chunking, and embedding.
- Experience in scaling GenAI or similar applications to accommodate a high number of users, large data size, and reduce response time.
- Must Have Skills: Python, AWS/Azure, Data Science, Gen AI tools (Azure Open AI, Langchain, vector DB), Software Engineering.
- Good to Have: DevOps, CI/CD, Kubernetes. Product development Experience.
What You’ll Bring
- Technical Proficiency: Demonstrated expertise in Python, AWS/Azure, Data Science, and GenAI tools (including Azure OpenAI, LangChain, and Vector DB), along with a strong foundation in software engineering principles.
- Advanced Skills in DevOps and CI/CD: Good to have experience in DevOps, Continuous Integration/Continuous Deployment (CI/CD), and Kubernetes is highly beneficial for enhancing product development and deployment processes.
- Product Development Experience: A background in product development is advantageous, enabling you to contribute to the creation of scalable, user-centric AI solutions.
- Ability to quickly adapt to new technology and be innovative in creating solutions
- Strong in at least one of the Programming languages - PySpark, Python or Java, Scala, etc. and Programming basics - Data Structures
- Experience in designing and implementation of solution on distributed computing and cloud services platform AWS, Azure, GCP.