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
- 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
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