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Job Details
Pay Rate: $62/hr
Lead a team of GenAI developers in designing, developing, and deploying cutting-edge generative AI models and applications that create significant business impact. Gen AI, Google Cloud Platform
Job Description:
We are seeking a seasoned and forward-thinking Generative AI Lead to drive our AI initiatives. The ideal candidate will possess extensive expertise in generative AI technologies, exceptional leadership abilities, and a demonstrated history of successfully delivering scalable AI solutions. In this role, you will lead a team of GenAI developers in designing, developing, and deploying cutting-edge generative AI models and applications that create significant business impact.
-Lead the complete development and deployment lifecycle of generative AI solutions on Google Cloud Platform, ensuring they align with business objectives and technical requirements.
-Develop and define the AI strategy and roadmap, emphasizing generative AI capabilities and their seamless integration into products and services.
-Supervise the design, fine-tuning, and optimization of large language models (LLMs) and other generative AI models across various applications.
-Manage and mentor a diverse team of AI developers and engineers, promoting a culture of collaboration and innovation.
-Work closely with cross-functional teams - engineering, and business stakeholders to translate requirements into effective AI solutions.
-Uphold best practices in AI ethics, data privacy, and model governance throughout the AI development lifecycle.
-Lead research and innovation efforts by keeping current with the latest developments in generative AI, multimodal models, and AI agents.
-Implement containerization and orchestration strategies using Docker and Kubernetes (GKE) for reliable deployment.
-Establish security frameworks using Azure Identity, Google Cloud Platform IAM, and other tools to ensure restricted and compliant access to AI systems.
-Monitor AI model performance in production, drive continuous improvement initiatives, and manage risks associated with AI outputs.
-Effectively communicate AI concepts, project progress, and business impact to both technical and non-technical audiences, including executive leadership.
-Knowledge of Cloud Storage, Cloud SQL, Cloud Spanner, Firestore, and Bigtable, including their use cases and configurations.
-Knowledge of real-time messaging and event-driven architectures like pub/sub.
-Familiarity with Cloud Functions, Cloud Run, and App Engine, and how to deploy and manage serverless applications.
-Familiarity with Google Cloud's Operations Suite, including Monitoring, Logging, Trace, Debugger, and Error Reporting to ensure system reliability and performance.