Lead AI Innovation Developer
Tasks
- Architect automation pipelines and workflows
- Build AI demos and proofs of value
- Build real time monitoring
- Define AI and platform architecture vision
- Define technical standards and integration frameworks
- Design AI/ML capabilities
- Ensure high availability and scalability
- Establish architecture best practices
- Evaluate emerging AI/ML technologies
- Evaluate model performance
- Implement AI guardrails
- Implement data ingestion pipelines
- Integrate AI frameworks and automation platforms
- Manage model lifecycle
- Mentor engineering teams
- Optimize platform performance and cost
- Recommend AI technologies for ROI
- Translate business needs into architectural designs
Perks/Benefits
Skills/Tech-stack
Agentic AI | Algorithms | Amazon Web Services | Appian | Automation Pipelines | Azure | Camunda | Cloud platform | Cost Optimization | CrewAI | Data Ingestion | Data Structures | Deep learning | Distributed Systems | Gemini AI | Google Cloud | Google Cloud Platform | High Availability | Langchain | Language Models | Language Processing | Large Language Models | Lifecycle Management | Machine Learning | Model Lifecycle | Model Lifecycle Management | N8n | Natural Language | Natural Language Processing | Pega | Prompt engineering | Pydantic | RAG | Real Time | Real-time monitoring | Retrieval-Augmented Generation | Scalable Architecture | Software Design | Web Services | Workflow automation
Education
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