GenAI Engineer1

Job Description:

Key Responsibilities

• Application Development: Code and integrate LLM APIs (OpenAI Anthropic etc.) or local models into backend services using Python FastAPI etc. OpenTelemetry logging.
• MCP Server Development: Design and implement custom MCP servers using the official SDKs (Python/TypeScript)to expose internal databases APIs and file systems to AI agents.
• RAG Implementation: Build & validate RAGspecifically coding the data ingestion scripts text chunking logic for optimal retrieval.
• Agent Development: Implement multi-step workflows using LangChain LangGraph CrewAI etc.focusing on tool-calling logic and error handling.
• Evaluation & Guardrails: Validate & finetune the solution you developed (correctness latency token optimization hallucination bias etc.). Coverage of common GenAI guardrails.
• Data Preparation: Prepare/finetune input data as needed.

Technical Skills (The Execution Stack)

• Language: Advanced Python(Asyncio Pydantic) and optional TypeScript/(for full-stack integration).
• AI Frameworks: Hands-on experience with any of LangChain LlamaIndex and Hugging FaceTransformers. RAG and Vector search concepts.
• Data Handling: Proficiency in SQLand handling other formats (PDFs Markdown JSON).
• Local Validation: Docker Experience as an end-user of CI pipelines to ensure compliance to quality.
• MCP/API Proficiency: Deep understanding of RESTful APIs Streaming HTTP MCP server vs client JSONRPC

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