Database Engineer

3-5 years of experience managing Microsoft SQL Server in production, both IaaS and PaaS. Strong experience with full-text and semantic search using Azure Cognitive Search and/or ElasticSearch. Experience building or maintaining RAG/LLM architectures, including vector stores, embedding generation, and retrieval APIs. Proficiency in tuning and debugging database performance (wait stats, execution plans, indexing). Hands-on experience with observability platforms and standards (OpenTelemetry, Grafana, APM tools, etc.). Automation scripting with PowerShell or Python. Proficiency with Infrastructure-as-Code (Bicep, Terraform, ARM templates). Familiarity with compliance, RBAC, and secure data practices in cloud environments. Bonus: experience instrumenting and debugging LLM inference chains or vector database retrieval quality.

Design, deploy, and operate Microsoft SQL Server workloads across Azure IaaS and PaaS. Build, scale, and tune AI Search and ElasticSearch clusters, pipelines, and relevance models. Collaborate with developers and ML teams to build retrieval pipelines for LLM applications. Integrate observability into all layers of the data/search stack. Analyze and optimize SQL queries and indexing strategies. Secure data access using encryption, private endpoints, and RBAC. Automate recurring operations using PowerShell/Azure DevOps Pipelines. Implement Infrastructure-as-Code (IaC) for SQL and search platforms using Bicep. Drive incident resolution and root cause analysis for issues across SQL, search, and LLM pipelines. Maintain technical documentation and operational runbooks.