Senior Manager, Gtm Sales Engineer & AI Solutions

Toast Toast · Enterprise · United States · Remote · Sales : Retail Sales Enablement

This role is for a Senior Manager, GTM Sales Engineer & AI Solutions at Toast, focused on driving AI integration within the Retail vertical to improve sales productivity. The role involves leading an AI GTM Pod, sourcing and scaling AI applications from experiments to production, evaluating build vs. buy options, and executing agile sprints for AI-powered features. Responsibilities include industrializing frontline wins with robust engineering practices, integrating AI outputs into core GTM platforms, ensuring data integrity, and implementing application security. The role also requires cross-functional partnership to align with enterprise AI strategies and personalize central tools for the Retail vertical.

What you'd actually do

  1. Stand up the Retail AI GTM Pod to surface, qualify, and scale AI applications across the Retail field.
  2. Serve as the production engine for ideas surfacing through the pod and field.
  3. Maintain and execute against a technical scrum board, operating on defined sprint cycles to continuously ship, test, and iterate on AI-powered features.
  4. 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).
  5. 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.

Skills

Required

  • Applied AI expertise
  • Salesforce integration
  • Snowflake integration
  • Taskray integration
  • Agile/Scrum methodologies
  • Software engineering best practices (error handling, version control, secure coding)
  • LLM risk mitigation (prompt injection, data exfiltration)
  • Data validation frameworks
  • Application security design
  • Technical discovery and evaluation (build vs. buy)
  • Roadmap prioritization
  • Cross-functional collaboration

Nice to have

  • Experience in Retail vertical
  • Experience with GTM operations

What the JD emphasized

  • technical, builder-focused role
  • own the centralized deployment of AI applications
  • scale them into production tools
  • autonomous engineering capabilities to construct vertical-specific pipelines
  • Industrializing Frontline Wins
  • Systems Integration
  • Data Integrity Architecture
  • Application Security
  • mitigation of LLM risks
  • secure coding practices
  • ensure builds meet Toast's security standards given system proximity to payment and customer data workflows

Other signals

  • AI integration across the enterprise
  • AI-powered productivity and automation
  • scaling them into production tools
  • industrializing frontline wins
  • systems integration