At JFrog, we’re reinventing DevOps to help the world’s greatest companies innovate -- and we want you along for the ride. This is a special place with a unique combination of brilliance, spirit and just all-around great people. Here, if you’re willing to do more, your career can take off. And since software plays a central role in everyone’s lives, you’ll be part of an important mission. Thousands of customers, including the majority of the Fortune 100, 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 in our journey?
We’re looking for our newest member of the Architects team at JFrog’s CTO Office, where you'll have the unique opportunity to contribute to 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 machine learning (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