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 productive 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.
Robust 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

Perks:
Provident Fund

Work Location: In person

📌 Genai Engineer Jaipur
🏢 KDK Software India
📍 Jaipur