The Role

We are currently hiring a highly skilled and motivated Generative AI Engineer for developing an LLM application. As a Generative AI Engineer, you will be responsible for developing and implementing cutting-edge Generative AI models to solve complex problems and drive innovation across our organization. You will work closely with software engineers, and product managers to design, build, and deploy AI-powered solutions that enhance our products and services.

Key Responsibilities

• AI Model Development: Design and develop a Generative AI model to automate cybersecurity tasks, such as threat detection, investigation, and remediation.
• Advanced AI Techniques: Implement NLP, machine learning, LLM, RAG, prompt engineering and autonomous AI agents to interpret and generate human-like responses to security threats.
• Model Training and Evaluation: Utilize large datasets to train and refine AI models, continuously evaluating and improving model performance based on analysts feedback and performance metrics.
• Research and Development: Stay informed on the latest advancements in AI, machine learning, data engineering, and cybersecurity, integrating new technologies into our solutions to maintain our competitive edge.
• Integration: Collaborate with the engineering team to seamlessly integrate the AI model and data infrastructure into our SaaS platform, ensuring scalability and robustness.
• LLM Application Observability and Evaluation: Familiarity with observability and evaluation platforms for LLM applications.
  
  

Requirements:

Requirements

• Demonstrable experience in developing Generative AI models and managing complex data infrastructures, with a strong background in LLM, RAG, autonomous AI agents, LangChain and LLAMAindex.
• Expertise in machine learning, NLP, and deep learning frameworks (e.g. PyTorch, Hugging Face, Sentence transformers).
• Skilled in programming languages such as Python.
• Exceptional analytical, problem-solving, and communication skills.
• Ability to thrive in a fast-paced startup environment and collaborate effectively with a cross-functional team.
• Master’s or PhD in Computer Science, Data Science, Cybersecurity, or a related field. - an advantage.
• Familiarity with cybersecurity principles and the common threat landscape - an advantage
• Proficiency in data engineering technologies and practices, including experience with SQL/NoSQL databases, data pipelines, and data storage solutions (e.g., HDFS, S3). - an advantage