Senior AI Integration Developer
Tasks
- Configure air gapped model deployment
- Define tool definitions for assistants
- Deploy locally hosted models
- Design and implement MCP server
- Develop AI assistant user interface components
- Develop MCP tool interfaces
- Develop system prompts and context management
- Document AI architecture and evaluation results
- Evaluate tool call accuracy and reliability
- Identify high-value AI use cases
- Implement evaluation frameworks for AI quality
- Integrate LLM inference endpoints
- Maintain backend Python services
- Use Docker for containerized services
Perks/Benefits
Skills/Tech-stack
Agentic AI | Automated testing | CI/CD | Docker | Error Recovery | Evaluation Frameworks | FastAPI | FastMCP | GPU benchmarking | Git | Langchain | Langgraph | Latency benchmarking | Llama.cpp | Local LLM | MCP | Model Context Protocol | Model selection | Node.js | Ollama | PostgreSQL | Prompt Tuning | Prompt engineering | Python | RAG | React | Regression testing | Retrieval-Augmented Generation | System Prompt | Tool chaining | TypeScript | Vector Database | Vector Search
Education
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