Full Stack Engineer

We’re hiring a hands-on full-stack engineer who moves fluidly across backend, frontend, and AI.

You might design a multi-tenant data model in the morning, ship a polished, data-dense dashboard

in the afternoon, and wire up an LLM- or ML-powered feature the next day. You’ll work directly with

the product owner, own features end to end, and build software that touches every restaurant’s

bottom line. This is a builder’s role on a lean team - high ownership, real AI, visible impact.

What you’ll build

• Multi-tenant backend & APIs powering real-time financial, labor, and cost analytics across

many brands and locations.

• Financial engines - budgeting and budget-period normalization, actual-vs-budget variance,

actual-vs-theoretical (AvT) food & beverage cost, and live hour-level P&L.

• Labor intelligence - sales-per-labor-hour targets, AI-assisted scheduling, and real-time labor

monitoring and alerts.

• AI features - a conversational “ask your restaurant anything” assistant, invoice/expense

anomaly detection, demand & sales forecasting, and menu-engineering analytics.

• Integrations with POS, payroll/labor, and accounting systems.
• Polished dashboards & interfaces built on our design system - fast, responsive, and datadense.

What you’ll do

• Design and build across the full stack - schemas, APIs, services, and UI - from spec to

production.

• Implement AI features end to end: LLM integration (prompting, tool/function calling, structured

outputs, RAG) and ML models (anomaly detection, forecasting), plus their evaluation and

guardrails.

• Engineer for multi-tenancy, performance, and correctness at network scale (thousands of

locations).

• Keep analytics deterministic, explainable, and auditable - our numbers must be provable,

not black boxes.

• Write clean, tested, documented code; partner with the product owner to turn use cases into

reliable features.

• Contribute to security, reliability, and compliance-readiness (SOC 2 / PCI-aware engineering)., building and deploying ML models (details below).
• Product mindset: you care about correctness, UX, and getting things into users’ hands.

AI implementation - what “hands-on” means here

You’ve shipped AI in production, not just prototyped it. Ideally you’ve done several of these:

AI experience we value

• Integrated LLM APIs into real features (assistants/chat, extraction, summarization) with

prompt design, tool/function calling, structured outputs, and evaluation/guardrails against

hallucination.

• Built or deployed ML models for tabular data - anomaly/outlier detection (e.g., Isolation

Forest), time-series forecasting, or classification - including feature engineering, validation,

and monitoring.

• Kept AI features explainable and trustworthy: confidence scoring, thresholds, human-inthe-loop escalation, and minimizing false positives.
• Comfortable reasoning about cost, latency, and accuracy trade-offs of AI features at

• 8+ years building and shipping production full-stack web applications.
• Frontend: strong with a modern framework (React / Vue / Svelte or similar),

TypeScript/JavaScript, and HTML/CSS; you build data-dense, responsive UIs (charts, tables,

dashboards) that feel fast and clean.

• Backend: strong in Node.js/TypeScript and/or Python - REST/GraphQL API design, services,

and authentication/authorization.

• Data: solid relational database and SQL skills (PostgreSQL preferred); comfortable designing

multi-tenant schemas and writing performant queries.

• AI: hands-on experience shipping AI in production - integrating LLMs into features and/or, * Domain experience in restaurants, hospitality, fintech, or ERP/accounting.
• Data pipelines / ETL, event-driven architectures, and third-party integrations (POS, payroll,

accounting).

• Cloud (AWS / GCP / Azure), containers, CI/CD, and infrastructure-as-code.
• SOC 2 / PCI / GDPR-aware engineering; multi-currency and internationalization.
• Data-visualization craft and design-system fluency., * An honest engineer - you surface gaps and risks early, write things down, and build things

you can stand behind.

• A clear communicator who can work directly with a product owner and translate use cases

into reliable, well-scoped features.

Pay: From $50.00 per hour