Description

Requirements:

• LLM integration:
  • OpenAI
  • Anthropic Claude
  • Gemini
• Prompt Engineering, Context Management, Function Calling
• RAG / Semantic Search / Embedding Pipelines
• Vector DBs:
  • Qdrant
  • Pinecone
  • Weaviate
  • pgvector
• LangChain, LlamaIndex, Semantic Kernel, or custom orchestration
• Agentic AI workflows / multi-step reasoning
• Python, Go, or TypeScript/Node.js
• REST / GraphQL APIs
• Neo4j / Knowledge Graphs
• Docker / Kubernetes
• Async / Event-Driven Architectures
• LLM observability, tracing, token usage, quality metrics

Responsibilities:

• Build scalable AI-enabled platforms and APIs
• Develop RAG and semantic search pipelines
• Design agentic AI workflows
• Build ingestion/enrichment pipelines for structured & unstructured data
• Optimize context management and grounding/citation strategies
• Partner with Product and Engineering teams on AI initiatives

Key Skills

Education

Any Gradute