About the roleThis is not a role where you will bolt AI onto an existing product as an afterthought. SqlDBM is rebuilding core workflows around AI — from how data architects design schemas to how engineers validate changes to how governance teams maintain compliance across enterprise environments.You will work at the intersection of .NET backend engineering and applied AI — building the systems that make AI a first-class, reliable, enterprise-grade capability inside one of the most technically demanding categories in data infrastructure.This role sits inside our dedicated AI group and reports directly to senior leadership. You will have a short line to product, architecture, and business decisions — no layers, no queue. The team is small by design, moves fast, and has direct visibility into enterprise customer needs.What makes this role differentYou are not building a chatbot. You are building AI infrastructure for enterprise data teams — systems that understand schema context, generate governed artifacts, and integrate into the workflows of the world's most sophisticated engineering organizations. The problems are hard. The customers are demanding. The work is meaningful.What you'll doYou will own and extend the backend systems that power SqlDBM's AI capabilities. Specific areas include:AI-assisted data modeling workflows — backend services that allow users to describe their data needs in natural language and receive accurate, governed schema outputContext-aware intelligence — systems that use the full richness of a user's data model, naming standards, and governance rules to produce AI output that is specific to their environment, not genericAutomated documentation and metadata generation — AI pipelines that analyze existing schemas and produce accurate, consistent business documentation at scaleIntegration with enterprise AI ecosystems — API layers that allow external AI agents and tools to call SqlDBM as a trusted source of schema contextConsumption tracking and orchestration — backend infrastructure that manages AI request routing, model selection, cost optimization, and usage meteringGovernance-aware AI workflows — systems that embed approval, validation, and compliance logic into AI-generated outputs before they reach productionMCP server development — building and extending SqlDBM's Model Context Protocol server so that external AI agents and LLM-based tools can use SqlDBM as a trusted, real-time schema authorityTech Stack includes:Our backend is built on modern .NET with a microservices architecture deployed on AWS. AI capabilities are built on top of major LLM providers via API, with proprietary prompt engineering, context management, and output validation layers that are core intellectual property of the platform.Qualifications5+ years of backend engineering experience with C# and .NETProficiency in EnglishStrong understanding of REST API design and asynchronous service architecturesExperience integrating with external APIs and managing complex data pipelinesComfort working with LLMs via API — understanding of prompt construction, context management, token economics, and output validationExperience building systems that handle variable, structured data — schemas, metadata, or similarStrong engineering fundamentals — testing, code review, system design, observabilityAbility to work independently in a remote-first, fast-moving engineering teamStrong PlusExperience with data modeling, database design, or data engineering toolingFamiliarity with enterprise data platforms — Snowflake, Databricks, dbt, or similarBackground building developer tools or platforms used by technical teamsExperience with agentic AI workflows, tool-use patterns, or AI infrastructureKnowledge of semantic layer concepts, ontologies, or structured metadata systemsFamiliarity with Model Context Protocol (MCP) — building or consuming MCP servers in agentic AI architecturesWhat We OfferCompetitive base salary and equity in a profitable, growing companyFully remote — work from anywhereDirect impact on product direction — small team, no layers, your work ships to enterprise customersWork on genuinely hard technical problems at the frontier of AI and enterprise data infrastructureCollaborative, engineering-driven culture that moves fast and trusts its peopleWhy nowSqlDBM is at an inflection point. We have enterprise customers, a profitable business, and a product that is becoming something significantly more powerful. The engineers who join now will shape what that means and build the systems that define the next chapter of data architecture tooling.
8 days ago