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 objectives
Collaborate with key organizational stakeholders to understand AI requirements and design end-to-end AI solutions
Explore and experiment with novel ML and AI techniques and architectures to drive innovation
Evaluate and recommend ML and AI tools and frameworks to enhance productivity and effectiveness
Ensure the scalability and reliability of LLM-based system architectures
Provide technical guidance and mentorship to development teams on AI and ML technologies and practices
Influence the AI priorities of the company. Your decisions will shape our future direction in AI, and have a significant impact on JFrog's AI initiatives
To be an AI Architect at JFrog you need…
A bachelor's degree or higher in Computer Science, Data Science, or a related field
Proven experience in developing LLM-based application architectures
Proficiency 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 Guardrails
Experience with cloud platforms, such as AWS, Google Cloud, or Azure
Proficiency in Python programming
Experience deploying LLM-based applications in a production environment
Excellent problem-solving and analytical skills
Strong communication skills and the ability to collaborate effectively in a team