AI Enablement Lead [gn] Data Intelligence
Tasks
- Define AI adoption success metrics
- Define AI enablement strategy
- Define AI tooling standards for semantic search and caching
- Design and maintain internal AI platforms
- Develop AI workshops documentation and knowledge sharing
- Establish LLMOps and MLOps practices
- Evaluate AI vendors models and open source technologies
- Implement model governance security and privacy controls
- Integrate generative AI and machine learning into data platform solutions
- Lead AI prototyping from proof of concept to production
- Monitor and evaluate AI models
- Optimize AI infrastructure performance and cost
Perks/Benefits
Skills/Tech-stack
API Gateway | Agentic AI | Automated testing | CI/CD | Caching | Docker | Generative AI | Go | Kubernetes | LLMOps | Langchain | Language Models | Large Language Models | Llamaindex | MLOps | Machine Learning | Milvus | Model Evaluation | Model Governance | Monitoring | PGVector | Performance optimization | Pinecone | Privacy | Prompt engineering | Python | RAG | Security | Semantic Search | Vector Databases
Education
N/A
Roles
AI | AI Enablement | AI Enablement Lead | Enablement Lead | Engineer | LLMOps Engineer | Lead | Learning Engineer | Machine Learning Engineer
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