Job Summary
We are looking for a solution architect who can help in developing new features of Arti/PruChat scaling up the system and managing deployments in different settings. Should be able to design and implement solutions using Retrieval Augmented-Generation (RAG) and Large Language Models (LLMs). The ideal resource is a strong developer that can optimize performance for latency costs concurrency while maintaining high accuracy and high security.
Responsibilities
Demonstrated experience in developing chatbot solutions.
Understanding of end-to-end solution patterns of chatbot solutions and related trade-offs.
Experience collaboratively working with stakeholders and technical team members in an agile environment.
Experience in chatbot interfaces and how they tie into backend systems.
Strong experience in cloud technologies such as AWS and Azure (AWS preferred).
Strong programming experience in languages such as Python NodeJS and Java.
Expertise in designing developing and deploying chatbot solutions.
Experience in developing and consuming APIs that interact with LLMs.
Experience with prompt engineering with LLMs and an understanding of advantages/limitations of different LLMs.
Experience with cloud environments such as AWS or Azure (AWS preferred).
Fluency in core concepts of RAG LLMs and prompt engineering are required.
Experience with traditional conversational AI platforms is a plus.
Strong understanding of aspects such as concurrency latency and trade-offs between high accuracy cost and high security.
Experience with end-to-end solution design to deployment process is a strong plus.