Key Responsibilities

- Integrate LLM APIs to build intelligent automation, parsing, and conversational AI solutions.
- Design and develop Retrieval-Augmented Generation (RAG) Pipelines .
- Build, manage, and optimize Vector Databases for efficient knowledge retrieval.
- Ensure data security , compliance, and high-performance AI architecture.
- Monitor and optimize AI model quality, latency, and operational cost .
- Collaborate with Product and Engineering teams to deliver scalable AI-powered SaaS features.

Experience Required

- 3+ years of backend development experience using Python, Go, or Node.js .
- Experience building LLM Applications using OpenAI, Claude, or Hugging Face .
- Hands-on experience with LangChain or LlamaIndex .
- Solid understanding of Retrieval-Augmented Generation (RAG) .
- Experience with Vector Databases such as Pinecone, Weaviate, or pgvector .




- Experience working with Cloud Platforms (AWS, GCP, or Azure) .
- Knowledge of APIs, Microservices, and Prompt Engineering .

Preferred

- Experience in FinTech or SaaS domain.
- Exposure to LLMOps and Model Fine-tuning .

Skills Required : Must Have

- Model Integration.
- Retrieval-Augmented Generation (RAG) Pipelines .
- Vector Database implementation and management.
- Security and Compliance best practices.
- AI Performance Monitoring and Optimization.

Preferred

- CI/CD for AI Applications.
- Observability for AI systems.

Education & Qualification

- B.Tech / BCA or Technical Certification.

Pay: ₹1,000,000.00 per year

Benefits :

- Provident Fund

Work Location: In person

📌 Genai Engineer (Llm) Python Rag Langchain Ai Integration (Jaipur)
🏢 KDK Software India
📍 Jaipur