Gen AI Architect

Job Description

Key Responsibilities Design and implement GenAI architectures leveraging Google Cloud and Gemini AI models Lead solution architecture and integration of generative AI models into enterprise applications Collaborate with data scientists engineers and business stakeholders to define AI use cases and technical strategy Develop and optimize prompt engineering, model fine tuning, and deployment pipelines Design scalable data storage and retrieval layers using PostgreSQL BigQuery and vector databases e.g.Vertex AI Search Pinecone or FAISS Evaluate third party GenAI APIs and tools for integration Ensure compliance with data security privacy and responsible AI guidelines Support performance tuning monitoring and optimization of AI solutions in production Stay updated with evolving trends in GenAI and GCP offerings especially related to Gemini and Vertex AI Required Skills and Qualifications Proven experience architecting AI and ML or GenAI systems on Google Cloud Platform Hands-on experience with Google Gemini Vertex AI and related GCP AI tools Strong understanding of LLMs, prompt engineering and text generation frameworks Proficiency in PostgreSQL, including advanced SQL and performance tuning Experience with MLOps, CI and CD pipelines, and AI model lifecycle management Solid knowledge of Python, APIs, RESTful services, and cloud native architecture Familiarity with vector databases and semantic search concepts Strong communication and stakeholder management skills Preferred Qualifications GCP certifications e.g., Professional Cloud Architect Machine Learning Engineer Experience in model fine-tuning and custom LLM training Knowledge of LangChain, RAG Retrieval Augmented Generation frameworks Exposure to data privacy regulations GDPR, HIPAA, etc. Background in natural language processing NLP and deep learning