Generative AI Architect

Summary

Join Tiger Analytics as a Generative AI Architect to lead the design, development, and implementation of cutting-edge generative AI solutions on Google Cloud Platform (GCP). You will leverage the power of generative models to drive innovation and solve complex business challenges. As a key member of the Data Engineering team, you will work with cross-functional teams to translate business needs into robust and scalable GenAI architectures. This role requires deep expertise in GCP AI/ML services and generative AI models. You will define and own the end-to-end architecture, develop a GenAI strategy, and implement GenAI solutions on GCP. The position offers significant career development opportunities in a fast-growing environment.

Requirements

• 12+ years of experience in designing and implementing large-scale AI/ML solutions
• 5+ years of hands-on experience working with Google Cloud Platform (GCP) AI/ML services (e.g., Vertex AI, GenAI Studio, AI Platform)
• Deep understanding of generative AI models, including LLMs, diffusion models, and GANs, and their practical applications
• Strong experience with data engineering pipelines and tools on GCP (e.g., Dataflow, Dataproc, BigQuery)
• Proficiency in programming languages relevant to AI/ML (e.g., Python)
• Ability to work independently and collaboratively in a fast-paced environment
• Experience with deploying GenAI models for specific use cases (e.g., content generation, code generation, synthetic data generation)
• Knowledge of responsible AI frameworks and ethical considerations in AI development
• Experience with MLOps practices and tools for deploying and managing ML models on GCP
• Experience with infrastructure-as-code (IaC) tools like Terraform or Cloud Deployment Manager on GCP
• Solid understanding of cloud security principles and best practices on GCP
• Ability to work in a large matrixed organization and steer the path to success
• Excellent communication, presentation, and interpersonal skills

Responsibilities

• Define and own the end-to-end architecture for generative AI applications and platforms on GCP, ensuring scalability, reliability, security, and cost-effectiveness
• Develop a clear GenAI strategy aligned with business objectives, identifying use cases and recommending appropriate GCP services and generative models
• Evaluate and select the most suitable generative AI models (e.g., large language models, diffusion models, generative adversarial networks) and frameworks for specific applications
• Design data pipelines for training, fine-tuning, and deploying generative AI models on GCP, considering data quality, governance, and security
• Establish best practices and architectural patterns for building and deploying GenAI solutions on GCP
• Demonstrate deep expertise in Google Cloud Platform AI/ML services, including Vertex AI, GenAI Studio, AI Platform, Cloud Storage, BigQuery, and other relevant GCP components
• Lead the implementation of GenAI solutions on GCP, providing technical guidance and support to engineering teams
• Design and implement infrastructure-as-code (IaC) for GenAI deployments on GCP using tools like Terraform or Cloud Deployment Manager
• Optimize GenAI model performance and inference on GCP infrastructure
• Ensure seamless integration of GenAI solutions with existing enterprise systems on GCP or hybrid environments

Benefits

Significant career development opportunities exist as the company grows