Note: The job is a remote job and is open to candidates in USA. SqlDBM is the leading cloud-native data modeling platform trusted by Fortune 500 enterprises across various sectors. They are seeking a Senior Software AI Engineer to work on backend systems that integrate AI into data modeling workflows, focusing on building robust and reliable AI capabilities for enterprise data teams.
Responsibilities
- You 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 output
- Context-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 generic
- Automated documentation and metadata generation — AI pipelines that analyze existing schemas and produce accurate, consistent business documentation at scale
- Integration with enterprise AI ecosystems — API layers that allow external AI agents and tools to call SqlDBM as a trusted source of schema context
- Consumption tracking and orchestration — backend infrastructure that manages AI request routing, model selection, cost optimization, and usage metering
- Governance-aware AI workflows — systems that embed approval, validation, and compliance logic into AI-generated outputs before they reach production
- MCP 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 authority
Skills
- 5+ years of backend engineering experience with C# and .NET
- Strong understanding of REST API design and asynchronous service architectures
- Experience integrating with external APIs and managing complex data pipelines
- Comfort working with LLMs via API — understanding of prompt construction, context management, token economics, and output validation
- Experience building systems that handle variable, structured data — schemas, metadata, or similar
- Strong engineering fundamentals — testing, code review, system design, observability
- Ability to work independently in a remote-first, fast-moving engineering team
- Experience with data modeling, database design, or data engineering tooling
- Familiarity with enterprise data platforms — Snowflake, Databricks, dbt, or similar
- Background building developer tools or platforms used by technical teams
- Experience with agentic AI workflows, tool-use patterns, or AI infrastructure
- Knowledge of semantic layer concepts, ontologies, or structured metadata systems
- Familiarity with Model Context Protocol (MCP) — building or consuming MCP servers in agentic AI architectures
Benefits
- Competitive base salary and equity in a profitable, growing company
- Fully remote — work from anywhere
- Direct impact on product direction — small team, no layers, your work ships to enterprise customers
- Work on genuinely hard technical problems at the frontier of AI and enterprise data infrastructure
- Collaborative, engineering-driven culture that moves fast and trusts its people
- Benefits - comprehensive insurance coverage for employees and their dependents — including medical, dental, vision, life, and both short- and long-term disability, parental leave, an employer-sponsored 401(k) retirement plan, and stock options.
Company Overview