Generative AI Architect

Tiger Analytics is pioneering what AI and analytics can do to solve some of the toughest problems faced by organizations globally. We develop bespoke solutions powered by data and technology for several Fortune 100 companies. We have offices in multiple cities across the US, UK, India, and Singapore, and a substantial remote global workforce.

We are looking for a highly skilled and visionary Generative AI Architect to lead the design, development, and implementation of cutting-edge generative AI solutions on Google Cloud Platform (GCP). As a key member of our Data Engineering team, you will be instrumental in leveraging the power of generative models to drive innovation, solve complex business challenges, and create transformative user experiences. You will work closely with cross-functional teams, including data scientists, machine learning engineers, product managers, and business stakeholders, to translate business needs into robust and scalable GenAI architectures on GCP.

Responsibilities:

Architectural Design and Strategy:

• 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.

GCP Expertise and Implementation:

• 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.

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.

Benefits

Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging, and entrepreneurial environment, with a high degree of individual responsibility.