The opportunity
Toast creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy.
What you'll do
Leadership & Facilitation: Stand up the Retail AI GTM Pod to surface, qualify, and scale AI applications across the Retail field. The model could be a working group of AI-forward reps, managers, and leaders organized around defined themes in Sales & Onboarding, contributing domain expertise and frontline signals. The pod functions as an intake mechanism and sounding board, surfacing field experiments, pressure-testing priorities, and keeping your roadmap grounded in what moves the business.
Idea & Solution Sourcing: Serve as the production engine for ideas surfacing through the pod and field. Evaluate what is worth scaling, determine the right build, buy, or borrow path, and take the strongest ideas from experiment to production tool—launching with Enablement to non-technical end-users and maintaining active ownership through adoption tracking, feedback, and iteration.
Build vs. Buy Evaluation: Lead technical discovery to determine the most efficient path for problem statements, assessing whether to build a custom agentic solution, stitch existing APIs, or coordinate with vendors to purchase a scalable product.
Roadmap Prioritization: Translate decisions into a sprint-based roadmap, prioritizing developments based strictly on their potential to drive vertical PPR and eliminate administrative friction.
Agile Sprint Execution: Maintain and execute against a technical scrum board, operating on defined sprint cycles to continuously ship, test, and iterate on AI-powered features.
Industrializing Frontline Wins: Take successful, unscaled local experiments (e.g., territory expansion scoring, contact discovery pipelines, multi-intent category parsers) and harden them with error handling, version control, scalable code, and secure coding practices like input validation, secrets management, and mitigation of LLM risks (e.g., prompt injection).
What they're looking for
- Systems Integration: Coordinate integration efforts to map vertical AI outputs into core GTM platforms (Salesforce, Snowflake, Taskray), ensuring local applications enhance rather than disrupt foundational enterprise pipelines.
- Data Integrity Architecture: Build & monitor data validation frameworks ensuring model inputs are pristine and outputs are entirely auditable and trusted by the field.
- Application Security: Design & enforce security controls for Retail AI applications, including authentication/authorization frameworks, secrets management, access controls on model outputs, and mitigations for LLM risks (prompt injection, data exfiltration). Ensure builds meet Toast's security standards given system proximity to payment and customer data workflows.
- Enterprise Collaboration: Contribute to cross-functional AI coordination cadences connecting Revenue Operations, Marketing AI, and Business Technology teams across Toast. Align on company-wide AI investments, advocate for Retail use cases and merchant requirements in shared roadmaps, and identify where central efforts can be leveraged, adapted, or extended. Serve as Retail's active voice in sequencing these shared initiatives while staying coordinated.