The Role
Design and maintain scalable ETL pipelines and serverless microservices, build vector database and knowledge-graph solutions, implement RAG pipelines, and integrate LLM capabilities using Azure AI Services.
Summary Generated by Built In
Job Description
- evelop and maintain scalable ETL pipelines for structured and unstructured data
- Design and implement serverless microservices using cloud native patterns
- Build and optimize data solutions using vector databases and knowledge graphs
- Collaborate with ML engineers to integrate large language model capabilities into production systems
- Implement retrieval augmented generation pipelines for advanced AI use cases
- Work with Azure AI Services to deliver reliable and scalable solutions
- Experience in Python development for backend or data engineering tasks
- Hands on experience with ETL pipeline design and implementation
- Familiarity with Azure infrastructure and cloud native services
- Understanding of microservices architecture and serverless computing
- Experience working with vector databases and data indexing solutions
Skills Required
- Experience in Python development for backend or data engineering tasks
- Hands on experience with ETL pipeline design and implementation
- Familiarity with Azure infrastructure and cloud native services
- Understanding of microservices architecture and serverless computing
- Experience working with vector databases and data indexing solutions
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The Company
What We Do
Increasingly helps retailers drive basket revenue and happier customers. The AI platform intelligently sells bundles and collections on-site, in-store, and in Google Shopping and Facebook ads. Typically growing AOV by +30%. Inspired by Amazons famous 'frequently bought together' feature, we create frictionless shopping experiences and bring Amazon-like precision to the rest of eCommerce.We believe in giving customers a super-convenient, hyper-relevant, online experience!
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