Applied AI Engineer - US
Tasks
- Build agent workflows in production
- Build scalable backend and frontend systems
- Debug production issues and improve reliability
- Design and deploy LLM-powered applications
- Develop prompt strategies and context management
- Implement evaluation frameworks for AI outputs
- Integrate and optimize LLM APIs
- Optimize latency cost and scalability
- Own unit integration and end to end testing
- Translate requirements into working solutions
Perks/Benefits
Skills/Tech-stack
Agent workflow | Anthropic API | CI/CD | End to End | End-to-End Testing | Gemini API | Google Gemini | Google Gemini API | Integration Testing | JavaScript | LLM | Langchain | Langgraph | OpenAI API | Prompt engineering | Python | RAG | Retrieval-Augmented Generation | Tool use | Unit Testing
Education
N/A
Roles
AI Engineer | Applied AI Engineer | Developer | Engineer | Full Stack | Full Stack Developer
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