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AI Platform Engineering Lead
2 weeks ago
The ideal candidate will have a deep understanding of platform development and deployment at the scale of large enterprises, as well as strong distributed systems skills and knowledge. They will be responsible for leading the design, development, and deployment of a generative AI platform, ensuring optimal integration with enterprise systems and standards.
Key responsibilities include:
- Hands-on development and architecture for a robust and scalable solution tailored to support AI-driven applications.
- Technical leadership and hands-on expertise in generative AI technologies and cloud architecture.
- Full-stack development of the platform for AI products, including custom architecture for batch and stream processing-based AI ML pipelines.
- Deployment, management of scalable and reliable platform and application infrastructure for AI, ML, GenAI, LLM products.
- Development, integration, and testing of scalable APIs.
- Robust monitoring systems to track model performance, data quality, and infrastructure health.
- Collaboration with data scientists, machine learning engineers, and software engineers.
- Implementation of security measures and compliance standards of the platform and APIs.
- Mentor technical engineering talent.
- Maintain documentation and architecture blueprints.
- Ensure the use of standards, governance, and best practices in ML pipeline and ML model monitoring.
The successful candidate will have a Bachelor's or master's degree in computer science, Engineering, or a related field, and 7+ years of hands-on cloud platform engineering experience preferably with AI/ML development experience. They will also have significant hands-on development experience in integrating, evaluating, deploying, operationalizing scalable full-stack and web-application solutions.