Generative AI Engineer

About the Role We are seeking a Generative AI Engineer focused on building and deploying production-grade AI solutions on Google Cloud Platform (GCP) and Vertex AI. The engineer will develop LLM applications, implement RAG architectures, integrate structured and unstructured data, and deliver AI-powered insights for business users. This role bridges Software Engineering, Machine Learning Engineering, and Generative AI, with a strong emphasis on cloud-native development and production deployment. Responsibilities Build and deploy Generative AI solutions using Google Vertex AI. Develop LLM pipelines that generate business insights from large datasets. Design and implement RAG (Retrieval-Augmented Generation) solutions. Perform prompt engineering and model optimization. Integrate AI capabilities into APIs, dashboards, analytics platforms, and data pipelines. Work with structured and unstructured data sources. Collaborate with business stakeholders to translate requirements into AI solutions. Stay current with advancements in LLMs, NLP, and Generative AI technologies. Communicate technical concepts to both technical and non-technical audiences. Qualifications Bachelor's degree in Computer Science, Computer Engineering, Mathematics, Statistics, or related quantitative discipline 2+ years of software engineering experience. 1+ year deploying solutions in cloud environments. Strong programming skills in Python (Flask), LangChain, Java (Spring) or C/C++ Cloud-based application deployment Strong communication and stakeholder engagement skills. Nice-to-have: Master's degree in a technical field Hands-on experience with Google Cloud AI technologies, including Vertex AI, GCP, BigQuery ML, Cloud Run, and AutoML Knowledge of AI/ML concepts, including NLP, Transformers, Deep Learning, and Diffusion Models Experience developing advanced GenAI solutions using RAG, Multi-modal AI, Fine-tuning, LoRA, and PEFT Familiarity with MLOps, model monitoring, and CI/CD pipelines for AI applications Experience working with large-scale data platforms such as Snowflake, Hadoop, AWS, or other Big Data environments Background in financial services, credit risk, or risk analytics Understanding of AI governance, regulatory compliance, GDPR, AI Act, and SEC requirements Show more Show less