Qdrant Developer

Position: Qdrant Developer

Duration: 12+ Months

Interview Mode: Virtual

Job Description

We are seeking a skilled Qdrant Developer with hands-on experience in vector databases and AI-powered search applications. The ideal candidate should have experience designing, implementing, and optimizing vector search solutions using Qdrant for Retrieval-Augmented Generation (RAG) and semantic search use cases.

Required Skills

• 3+ years of software development experience with Python.
• Hands-on experience with Qdrant Vector Database.
• Strong understanding of vector embeddings and semantic search.
• Experience with embedding models such as OpenAI, Sentence Transformers, or Hugging Face.
• Knowledge of RAG (Retrieval-Augmented Generation) architectures.
• Experience integrating Qdrant with LLM frameworks such as LangChain or LlamaIndex.
• Familiarity with REST APIs and microservices.
• Experience with Docker and Kubernetes is a plus.
• Knowledge of cloud platforms (AWS, Azure, or Google Cloud Platform).
• Strong problem-solving and debugging skills.

Responsibilities

• Design, develop, and maintain vector search solutions using Qdrant.
• Build and optimize semantic search and RAG pipelines.
• Create and manage vector collections, indexing, and embeddings.
• Integrate Qdrant with AI/ML applications and LLM frameworks.
• Optimize search performance, scalability, and data retrieval.
• Collaborate with AI engineers, data scientists, and application developers.
• Monitor, troubleshoot, and improve vector database performance.

Preferred Qualifications

• Experience with Generative AI and Large Language Models (LLMs).
• Knowledge of FastAPI or Flask.
• Experience with Git, CI/CD, and Agile development methodologies.
• Bachelor's degree in Computer Science, Engineering, or a related field.