Database Engineer RAG Platform Developer
Job Location:
Job Location:
Austin, TX - USA
Monthly Salary:
Not Disclosed
Monthly Salary:
Posted on:
4 hours ago
Posted on:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
Were seeking a Database Engineer to architect and optimize our large-scale RAG (Retrieval-Augmented Generation) platform that serves our users across all of the Hardware Tech group. This role combines deep database expertise with modern AI/ML infrastructure enabling design teams to seamlessly onboard and query enterprise-scale datasets. Youll be responsible for database architecture and optimization while also contributing to full-stack GenAI application development.
As a Database Engineer on our team you will architect and optimize our SQL and vector database infrastructure supporting enterprise-scale design data. Youll lead technical decisions on database architecture scaling patterns and technology selection for our RAG platform while designing comprehensive strategies to ensure optimal performance. Working closely with the development team youll build and refine data ingestion pipelines that enable design teams across all disciplines to seamlessly onboard their data. Youll collaborate with DevOps/SRE teams to ensure quality of service proper resource allocation and system scalability while improving RAG retrieval performance through hybrid search strategies index tuning and embedding addition to your primary database focus youll contribute to full-stack development using Python and JavaScript monitor database health and performance metrics for our multi-tenant system and develop and maintain database operations procedures monitoring and disaster recovery strategies while driving continuous improvement of retrieval quality search latency and overall system reliability. Youll also provide mentorship to other engineers on database best practices and scalable design patterns.
Proficiency in Python or experience deploying and managing vector databases (Milvus Qdrant or Weaviate) at scalenExperience with PostgreSQL or MySQL in production environmentsnUnderstanding of RAG pipelines including embedding strategies chunking and retrieval optimizationnMinimum requirement of BS 10 years of relevant industry experience
Understanding of Vector database indexing strategies and tradeoffsnStrong SQL proficiency with deep understanding of query planning indexing strategies and optimization techniquesnPostgres advanced features (extensions replication sharding)nExperience managing large-scale databases serving high-concurrency workloadsnExperience with embedding models and LLM integration patternsnDemonstrated experience building or optimizing RAG systems in production environmentsnCollaborative mindset with ability to mentor engineers and work closely with DevOps/SRE teamsnMonitoring and observability tools (Prometheus Grafana)nKubernetes experience particularly with stateful applications and database deploymentsnProven ability to make architectural decisions for scalable database systems
As a Database Engineer on our team you will architect and optimize our SQL and vector database infrastructure supporting enterprise-scale design data. Youll lead technical decisions on database architecture scaling patterns and technology selection for our RAG platform while designing comprehensive strategies to ensure optimal performance. Working closely with the development team youll build and refine data ingestion pipelines that enable design teams across all disciplines to seamlessly onboard their data. Youll collaborate with DevOps/SRE teams to ensure quality of service proper resource allocation and system scalability while improving RAG retrieval performance through hybrid search strategies index tuning and embedding addition to your primary database focus youll contribute to full-stack development using Python and JavaScript monitor database health and performance metrics for our multi-tenant system and develop and maintain database operations procedures monitoring and disaster recovery strategies while driving continuous improvement of retrieval quality search latency and overall system reliability. Youll also provide mentorship to other engineers on database best practices and scalable design patterns.
Proficiency in Python or experience deploying and managing vector databases (Milvus Qdrant or Weaviate) at scalenExperience with PostgreSQL or MySQL in production environmentsnUnderstanding of RAG pipelines including embedding strategies chunking and retrieval optimizationnMinimum requirement of BS 10 years of relevant industry experience
Understanding of Vector database indexing strategies and tradeoffsnStrong SQL proficiency with deep understanding of query planning indexing strategies and optimization techniquesnPostgres advanced features (extensions replication sharding)nExperience managing large-scale databases serving high-concurrency workloadsnExperience with embedding models and LLM integration patternsnDemonstrated experience building or optimizing RAG systems in production environmentsnCollaborative mindset with ability to mentor engineers and work closely with DevOps/SRE teamsnMonitoring and observability tools (Prometheus Grafana)nKubernetes experience particularly with stateful applications and database deploymentsnProven ability to make architectural decisions for scalable database systems
Required Experience:
IC
About Company
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