AI Architect - W2 only

2 weeks ago Be among the first 25 applicants Get AI-powered advice on this job and more exclusive features. Duration: Long term Description: Must Have skills: AI Architect with chatbot, GEN AI experience Position Summary: Develop new functionality of our GenAI platform and help support end-to-end use cases. Develop solutions by utilizing solid understanding of the architectural principles in chatbots for knowledge management, and self-service functionality by invoking APIs for validation, request completion, etc. Translate business needs into working solutions aligned with enterprise architecture. Design and implement solutions using Large Language Models (LLMs) using direct APIs to LLMs, and also via solutions such as Retrieval Augmented-Generation (RAG). Optimize performance for latency, costs, concurrency, while maintaining high accuracy and high security. Use your understanding of the structure of various backend systems, such as authentication, authorization, enterprise databases, enterprise APIs, etc., in the context of an end-to-end solution. Assess end-to-end design and performance. Implement current trends and best practices in AI/ML. Collaborate with cross-functional Agile teams to deliver new functionality and use cases within the chatbot platform. Work closely with stakeholders, tech-leads, and product owners on prioritized features. Will work on designing solutions, developing code, and assist junior members on implementation details and code reviews.

Required Qualifications Understanding of end-to-end solution patterns of chatbot, Gen AI solutions and related trade-offs. Experience collaboratively working with stakeholders and technical team membersin an agile environment. Experience in chatbot interfaces and how they tie into backend systems. Strong programming experience in languages such as Python, NodeJS, and Java. Experience 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. Bachelor's degree in computer science, engineering, information technology, artificial intelligence, or a related field. (or equivalent professional experience) Desired Qualifications Strong analytical mindset with proven technical analysis and research, problem-solving skills, and diagnostic ability Experience with Maven, Jenkins, BitBucket, Kendo, Horizon are plus Experience working with teams in different locations, co-ordination of tasks Experience working in an Agile development methodology Setting up CI/CD automation Experience working with Build tools (JIRA, Bit Bucket, Maven, Git, Horizon, and Jenkins, or other containerized runtime environment) Seniority level

Seniority level Mid-Senior level Employment type

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