Senior Applied AI Engineer - Energy Industry
Raleigh, US, North Carolina
USD 146K-183K (estimate) Senior-level Full Time
Tasks
- Architect and deliver LLM agent systems with RAG
- Deliver pre sales solution demonstrations
- Develop AI roadmaps and ROI TCO business cases
- Guide post sale implementation and value realization
- Implement security scalability and guardrails
- Integrate solutions with enterprise data and identity protocols
- Lead technical discovery for energy customers
- Present demos and technical readouts to executives
- Prototype generative AI solutions in customer hackathons
Perks/Benefits
- Company equity (RSUs)
- Comprehensive benefits
- Counseling
- Gym subsidies
- Hybrid work
- Learning program
- Mentorship
- Paid time off
- Parental leave
- Volunteer days
- Well-being programs
Skills/Tech-stack
AWS Bedrock | Access Management | Agent Orchestration | Azure AI | Data integration | Few-Shot Learning | Few-shot | Fine Tuning | Function Calling | Generative AI | Google Cloud | Google Cloud Vertex | Google Cloud Vertex AI | Identity and Access Management | Identity and access | Langchain | Language Models | Large Language Models | Llamaindex | Machine Learning | Model Monitoring | Multi-Agent | Multi-agent orchestration | Pandas | Process mining | Prompt engineering | Prompt evaluation | PyTorch | Pydantic | Python | RAG | Safety Guardrails | Scikit-learn | Vertex AI
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
Regions
Countries
States
Cities
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