CyberArk is seeking an AI Developer to design and implement AI-driven solutions as part of their internal Transforming How We Work program, aiming to build applications and pipelines that leverage large language models (LLMs) and enterprise data to drive intelligent automation and insights across the company.
Requirements
- 3+ years of experience in software development or AI/ML engineering, with a track record of building or implementing AI-driven solutions.
- Demonstrated experience working with large language models and natural language processing, including fine-tuning models and applying retrieval-augmented generation techniques to ground AI outputs in relevant data.
- Strong ability to analyze complex data and model performance metrics, identifying and resolving issues to improve outcomes.
- You care about best practices and what it takes to write and maintain great code
- You care about managing technical debt
- You get end-to-end with solutions early to de-risk them
- You love to quickly adopt new tools and languages
Responsibilities
- Design and Develop AI Solutions: Build and implement AI-powered applications and workflows on the internal AI platform that solve business problems and improve efficiency.
- Fine-Tune LLMs: Customize and fine-tune large language models (e.g., GPT-style models) to address specific use cases and improve their performance for CyberArk’s needs.
- Knowledge Grounding & Retrieval: Develop and optimize retrieval-augmented generation (RAG) pipelines, incorporating efficient retrieval systems to ground LLM outputs in accurate, up-to-date internal data.
- Create and maintain indexes (e.g., embedding vectors, knowledge bases) that enable fast and relevant information retrieval for AI solutions.
- Collaborative Solution Building: Work closely with data scientists and the AI Machine Learning Engineer to integrate machine learning models into end-to-end solutions.
- Coordinate with the AI Platform Architect to ensure your solutions align with architectural standards for security, scalability, and governance, and with the AI Infrastructure Engineer to deploy, monitor, and maintain these AI solutions in production environments.
- Testing and Iteration: Rigorously test AI models and applications, validate their accuracy and effectiveness (including handling of edge cases), and iterate based on feedback and performance metrics.
Other
- Bachelor’s degree in computer science, engineering, or a related field.
- Feedback loops – especially with real users – are a highly valued asset
- You have curiosity about the AI landscape and continuously learn
- We are unable to sponsor or take over sponsorship of employment Visa at this time.
