Generative AI Engineer

Company Description
Lumenore is an AI-driven analytics platform that makes data accessible by allowing users to ask questions in plain language and instantly uncover actionable insights. The platform offers no-code dashboards, 80+ data connectors, and predictive analytics to help organizations transform raw data into strategic outcomes. Lumenore serves executives, teams, and developers by enabling them to scale insights and embed analytics directly into their products. Trusted by clients worldwide, the company focuses on clarity, speed, and precision in decision-making, helping businesses unlock the full value of their data.
Role Description
The Generative AI Engineer will design, build, and optimize AI models that power natural language querying, insight generation, and intelligent automation within Lumenore’s analytics platform. In this full-time remote role, the engineer will develop and fine-tune large language models, integrate them with data pipelines and APIs, and collaborate with product, data, and engineering teams to deliver robust, user-centric AI features. Typical responsibilities include experimenting with model architectures, improving model accuracy and latency, implementing evaluation frameworks, and ensuring responsible AI practices around privacy, fairness, and security. The Generative AI Engineer will also contribute to technical documentation, support production deployments, and continuously monitor and refine models based on real-world performance.
Qualifications
Strong proficiency in Python and common ML/AI frameworks (e.g., PyTorch, TensorFlow, Hugging Face Transformers) for building and deploying generative models.
Experience with large language models (LLMs), prompt engineering, fine-tuning, RAG pipelines, and NLP techniques such as text generation, summarization, and question answering.
Solid understanding of machine learning fundamentals, including model training, evaluation, optimization, and MLOps practices for production-scale AI systems.
Hands-on experience with cloud platforms and data tools (e.g., AWS, Azure, GCP, Docker, Kubernetes, SQL/NoSQL databases, vector databases) for scalable AI deployment.
Background in software engineering best practices, including version control (Git), testing, CI/CD, API development, and performance optimization.
Ability to collaborate effectively in cross-functional remote teams, communicate complex technical concepts clearly, and translate business needs into AI solutions.
Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field, or equivalent practical experience.
Experience with analytics or BI platforms, data visualization, and responsible AI principles (privacy, ethics, bias mitigation) is highly beneficial.

Work arrangement
Yes