AI Database Engineer

We are looking for a Production-First Database Engineer to bridge a critical gap in our largest data footprint (SQL Server) while building Agentic AI frameworks to automate database operations.

We aren't looking for "prompt engineers" or data pipeline providers; we need a builder who can develop autonomous agents that reduce manual toil with strict production guardrails.

🎯 Key Responsibilities

SQL Server Specialist: Act as the primary SME for our largest database footprint (10x larger than Postgres/Oracle combined). Own High Availability (AlwaysOn), performance tuning, and disaster recovery.

Agentic AI Development: Build and deploy autonomous AI agents (using frameworks like LangChain, CrewAI, or AutoGen) for automated incident triage, log analysis, and self-healing workflows.

Operational Leverage: Move beyond simple automation (n8n) to create AI-driven tools that interact with internal APIs and telemetry to eliminate repetitive manual work.

🚫 What This Role Is NOT

Not a Data Science/ML Research role: You won't be training LLMs from scratch.

Not a "Prompting" role: We need someone who builds the logic under the prompt.

Not a Reactive DBA: This is an engineering role focused on systemic improvements.

🎓 Required Qualifications

Deep SQL Server Expertise: 5+ years managing mission-critical SQL Server environments. You must understand internals, locking, and optimization at a granular level.

Agentic AI Foundation: Proven experience building at least "the smallest AI automation." You must be able to discuss specific models and frameworks used (beyond just API calls).

Engineering Mindset: Strong Python/Scripting skills and experience operating cloud-native databases in AWS or Azure.