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OpenTable

Principal Software Engineer - Agentic Engineering Platform

Toronto, Canada; Toronto OfficeCanada
Principal · Product Engineering
POSTED 3 NOVVERIFIED 1H AGO
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Open for
0d
since 3 Nov
H-1B · FY26
7
1 PERM
Hiring · 30d
110
−2 net · open roles
Distributed systems

With millions of diners, 70,000+ restaurant partners and 25+ years of experience, OpenTable, part of Booking Holdings, Inc. (NASDAQ: BKNG), is an industry leader with a passion for helping restaurants thrive. Our world-class technology empowers restaurants to focus on what matters most – their team, their guests, and their bottom line – while enabling diners to discover and book the perfect restaurant for every occasion.

Every employee at OpenTable has a tangible impact on what we do and how we do it. You’ll also be part of a global team and its portfolio of metasearch brands. Hospitality is all about taking care of others, and it defines our culture.

About the job

As a Principal Engineer, you'll be a founding member of OpenTable's Agentic Engineering Platform team within Product Engineering, rethinking how software gets built. Our goal is to redesign the full product delivery workflow so people and AI agents can work together in shared team spaces, automate more of the work, and reduce the total cost of delivery. Today, fragmented context, inconsistent standards, and legacy infrastructure limit what agents can complete on their own. You'll build shared cloud agents and tools that connect company knowledge and engineering systems, with the testing, review, and rollout controls needed to use them safely. Working directly with product engineering teams, you'll help turn advances in AI into ways of working that let OpenTable take on more projects.

Responsibilities

  • Identify consequential bottlenecks in how teams deliver software. Use data and direct observation to choose valuable problems, define success, and lead the work through adoption.
  • Design, build, integrate, and operate shared cloud agents and developer tools that connect AI models with company knowledge, codebases, APIs, and engineering systems, giving agents the context they need to complete useful work.
  • Improve the full workflow across planning, implementation, testing, review, rollout, and production feedback. Question unnecessary steps and build automation that makes human and agent collaboration more effective.
  • Work directly with product engineering teams to learn their domains, pilot solutions, and respond to feedback. Package tools, context, and guidance so teams can use them independently.
  • Make unattended agent work dependable through permissions, isolated execution, automated testing and review, failure recovery, and cost controls. Set rollout checks based on risk, and record agent activity and outcomes so teams can trace work from request through production.
  • Test new AI capabilities in short experiments and act with urgency. Measure delivery time, quality, review effort, and total cost; share what you learn and stop or replace approaches when the evidence changes.

Minimum Qualifications

  • 8+ years of software engineering experience, including independently delivering and operating production systems used by others, making technical decisions, debugging failures, and working across unfamiliar codebases, APIs, databases, and cloud services.
  • Deep understanding of API design, service-oriented architecture, scalability, and security.
  • Strong proficiency with current AI coding tools such as Claude, Codex, or Cursor, and sound judgment about context management, model selection, and limits on what agents can do without human review.
  • Ability to reason from first principles, learn an unfamiliar business domain, and turn an ambiguous problem into a useful experiment and a working solution.
  • Evidence of helping other engineers adopt a tool or way of working through listening, collaboration, clear communication, and follow-through.

Preferred Qualifications

  • Experience building and deploying agents and shared engineering tools.
  • Production experience with cloud infrastructure, service identity, permissions, isolated execution environments, and distributed systems.
  • Experience with automated testing, evaluations of agent behavior, tracing, and observability tools.
  • Experience taking a prototype into sustained use across multiple teams, with evidence of improvements to delivery, reliability, or cost.
Source · OpenTableFirst seen 3 NovOriginal ↗