Principal Software Architect, Data/AI/ML

Restaurant365 is a SaaS company disrupting the restaurant industry! Our cloud-based platform provides a unique, centralized solution for accounting and back-office operations for restaurants. Restaurant365’s culture is focused on empowering team members to produce top-notch results while elevating their skills. We’re constantly evolving and improving to make sure we are and always will be “Best in Class” ... and we want that for you too!
The Principal Software Architect, Data/AI/ML is a senior technical leader responsible for the core data architecture that powers Restaurant365’s analytics, reporting, and AI capabilities. This is not an internal reporting or corporate BI role, it is a product platform architect role focused on how data and AI become differentiated value inside the R365 product ecosystem. You’ll drive the design for shared data services and platforms (data models, pipelines, warehouses/lakehouses, semantic layers, and ML/AI enablement), with Snowflake as a critical part of our modern data stack, ensuring they are secure, scalable, governed, and reusable across product lines. This role combines deep hands-on data and AI/ML architecture expertise with cross-functional leadership, driving modernization of legacy data assets, platform decomposition, and technical standards that enable teams to deliver data-driven and intelligence-powered features faster with higher quality. 

How you'll add value:

• Define and enable data architecture and engineering standards across Product Lines, ensuring consistent patterns for modeling, storage, access, governance, and responsible AI/ML usage. 
• Lead data-focused architecture reviews and technical governance for new products, platform initiatives, and AI/ML solutions, with particular emphasis on scalable, secure use of Snowflake and related cloud data services. 
• Own the reference architectures for enterprise data platforms, including Snowflake-based warehouses/lakehouses, streaming/real-time data, semantic models, and analytics/BI consumption patterns used across product teams. 
• Partner with Product, Engineering, Infrastructure, and Security to design data platforms that support analytics, reporting, operational workloads, and AI/ML use cases, ensuring clear data contracts and safe pathways for AI feature development. 
• Drive modernization of legacy schemas, ETL/ELT pipelines, and reporting stacks into scalable, cloud-native data and AI platforms with clear service and data domain boundaries, leveraging Snowflake and modern orchestration tooling where appropriate. 
• Define and promote patterns for data contracts, event-driven architecture, and CDC/streaming feeds that enable reliable, low-latency data sharing across systems and make high-quality data continuously available for AI/ML workloads. 
• Establish standards and best practices for data quality, lineage, observability, cataloging, and governance (including privacy, security, and compliance requirements) so AI/ML features are built on trustworthy, well-understood datasets. 
• Partner with AI and engineering teams to design data and feature platforms that power modern AI workloads (e.g., feature stores, vector search, retrieval-augmented generation, and model-serving integrations), including how these are realized on Snowflake and adjacent services. 
• Anticipate long-term risks in data growth, performance, reliability, and cost (including Snowflake usage and storage/compute patterns), and design solutions that prevent systemic issues across products and environments. 
• Mentor architects, principal engineers, and data engineers across teams, raising organizational maturity in data and AI architecture and accelerating adoption of shared patterns for Snowflake, data contracts, and AI/ML enablement. 
• Operate as a trusted technical advisor to executives and senior leaders, translating data and AI architecture decisions into clear business value, risk tradeoffs, and roadmap implications. 
• Represent the company in data and AI technical communities, helping position Restaurant365 as a leading data-driven and AI-enabled SaaS platform. 

What you'll need to be successful in this role:

• BS/MS in Computer Science or equivalent professional experience. 
• 14+ years of engineering experience, including significant experience designing and delivering large-scale data platforms and distributed systems. 
• Proven leadership in data and/or analytics architecture, engineering standards, and cross-functional collaboration across product, engineering, and infrastructure teams. 
• Recognized expertise in multiple data domains, such as data warehousing/lakehousing, data modeling, streaming/event-based architectures, and analytics/BI enablement. 
• Deep experience with modern data platform technologies, including hands-on archi