Senior Applied AI Engineer - CPGR
Tasks
- Build RAG based systems
- Build ROI TCO business cases
- Create prompt engineering solutions
- Define AI roadmaps
- Demonstrate prototypes to executives
- Design secure scalable LLM agent architectures
- Execute proof of value projects
- Integrate with enterprise data identity and compliance frameworks
- Lead technical pre-sales
- Orchestrate LLM agents
- Prototype machine learning and generative AI solutions
- Support implementation adoption and value realization
Perks/Benefits
- Company equity (RSUs)
- Comprehensive benefits
- Counseling
- Generous PTO
- Gym subsidies
- Hybrid working options
- Parental leave
- Volunteer days
- Well-being programs
Skills/Tech-stack
AWS Bedrock | Agent Orchestration | Azure AI | Data Engineering | Few-Shot Learning | Few-shot | Fine Tuning | Function Calling | Generative AI | Google Cloud | Google Cloud Vertex | Google Cloud Vertex AI | Langchain | Llamaindex | Machine Learning | Model Deployment | Model Monitoring | Multi-Agent | Multi-agent orchestration | Multimodal Understanding | Pandas | Prompt engineering | PyTorch | Pydantic | Python | RAG | Scikit-learn | Vertex AI
Education
Roles
AI | AI Engineer | Applied AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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