Senior Technical R&D Operations Manager

Toast•Boston, MA

27d•Remote

About The Position

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. Toast R&D is building an AI-native operating layer for how we plan, execute, and learn. This role will help design and build that foundation from the ground up. You will turn messy, manual workflows into structured, automated, and continuously improving systems—leveraging agent-first workflows, integrations, and low-code/no-code builder tools to build standalone applications to solve R&D org-wide problems. Rather than simply administering tools, you will architect how work flows across Jira, JPD, our internal beta testing platform, and adjacent systems—ensuring data integrity, automation by default, and real-time operational insight. This is a builder role: you will identify friction, prototype quickly (often with AI coding tools like Cursor or Claude Code), ship to production, measure impact, and harden what works. This role sits within the R&D Operations team at Toast. We empower teams to build great products efficiently and at scale by removing obstacles, fostering alignment, and equipping teams with the right processes, systems, and insights.

Requirements

8+ years of experience in Technical Operations, Systems Engineering, Product Operations, Platform Engineering, or a similar role within a software or R&D organization.
Demonstrated experience building and shipping AI-native systems & custom tools — including hands-on work with AI coding environments (e.g., Claude Code, Cursor) and agentic workflows.
Experience designing multi-step AI systems that retrieve context, reason, generate outputs, and take bounded action.
Strong systems thinking: ability to design end-to-end workflows across tools, APIs, data models, and automation layers.
Experience integrating systems via APIs and building event-driven automation.
Experience designing human-in-the-loop controls and safe autonomy guardrails.
Strong cross-functional partnership skills and the ability to translate operational friction into production-grade systems.
Clear, concise communicator able to explain technical concepts to both technical and non-technical stakeholders.

Nice To Haves

Track record of independently identifying operational friction and implementing durable, automation agentic AI-first solutions at scale.
Background operating in a high-growth or high-complexity SaaS environment where systems and governance needed to scale alongside the organization.

Responsibilities

Optimizing and instrumenting the existing R&D operating system.
Architect automation-first workflows across Jira, JPD, internal beta systems, and adjacent tools.
Design structured data models and guardrails so systems stay clean by default — not through manual enforcement.
Eliminate recurring manual work through event-driven automations and API integrations.
Instrument workflows to generate operational telemetry (cycle time, bottlenecks, throughput).
Build reusable automation patterns that scale beyond one-off fixes.
Treat tool administration as a fallback — system design and automation as the default.
Help create the AI platform layer that improves how R&D operates.
Design and deploy agent-first workflows where AI systems execute meaningful portions of work autonomously within defined boundaries.
Use AI-native development environments (e.g., Claude Code, Cursor) as daily drivers to prototype and productionize agents and internal AI tools.
Architect multi-step agent systems that retrieve context, reason across structured and unstructured data, generate outputs, and take bounded action.
Establish safe autonomy standards: scoped permissions, observability, evaluation loops, and human escalation paths.
Ship quickly, measure impact, and harden what works.