AI Architect - Platform Infrastructure (Gen AI application team)

At JFrog, we're reinventing DevOps to help the world's greatest companies innovate - and we want you along for the ride. This special place has a unique combination of brilliance, spirit, and all-around great people. At JFrog, if you're willing to do more, your career can take off. With software at the heart of everyone's lives, you'll be part of an important mission. Thousands of customers, including most of the Fortune 500, trust JFrog to manage, accelerate, and secure their software delivery from code to production - a concept we call "liquid software." Wouldn't it be amazing if you could join us on this journey?We're looking for a hands-on AI Architect to join JFrog's Platform infrastructure (Gen AI applications team) where you'll have the unique opportunity to collaborate with JFrog's strategic technical leadership and the development of next-generation technologies for modern software release management, driving the industry forward.As an AI Architect at JFrog you will...Design, develop, and implement various ML and AI-based solutions to address business needs and objectivesCollaborate with key organizational stakeholders to understand AI requirements and design end-to-end AI solutionsExplore and experiment with novel ML and AI techniques and architectures to drive innovationEvaluate and recommend ML and AI tools and frameworks to enhance productivity and effectivenessEnsure the scalability and reliability of LLM-based system architecturesProvide technical guidance and mentorship to development teams on AI and ML technologies and practicesInfluence the AI priorities of the company. Your decisions will shape our future direction in AI, and have a significant impact on JFrog's AI initiativesTo be an AI Architect at JFrog you need…A bachelor's degree or higher in Computer Science, Data Science, or a related fieldProven experience in developing LLM-based application architecturesProficiency in ML along with relevant tools, processes, and frameworks, such as TensorFlow, PyTorch, Keras, natural language processing (NLP), and reinforcement learning from human feedback (RLHF)Proficiency in LLM-related tools, processes, and frameworks, including OpenAI Models and APIs, Hugging Face Transformers, LangChain, vector databases, and prompt management tools like PromptPerfect/PromptBase and GuardrailsExperience with cloud platforms, such as AWS, Google Cloud, or AzureProficiency in Python programmingExperience deploying LLM-based applications in a production environmentExcellent problem-solving and analytical skillsStrong communication skills and the ability to collaborate effectively in a team