Experience Level 8 Plus years with at least 2 to 3 years in AI/ML/GenAI
Primary Skill: Google Gemini, GCP, Vertex AI
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
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