Lead Forward Deployed Engineer, Hospitality

telostravel.ai Lead Forward Deployed Engineer, Hospitality Remote (US or Canada) · Hybrid/Remote · Reports to the Chief Operating Officer About telos telos is an AI revenue decision platform: a decision-infrastructure layer that sits between systems of record (PMS, CRS, RMS, distribution) and the people making high-yield commercial decisions on pricing, inventory, mix, and merchandising. We amplify the judgment of revenue teams by surfacing more good decisions than any team has time to find on its own. Our airline business is live in production with major carriers, and we are now building the equivalent capability for hospitality. This role delivers it, hotel by hotel and brand by brand. The Role Forward deployed engineers at telos ship working AI inside client environments. As Lead Forward Deployed Engineer, you sit at the intersection of hotel revenue management practice and applied AI engineering. You embed with hotel commercial teams, own end-to-end delivery on their real data and real systems and stay until revenue managers trust the output enough to act on it. The hard part of AI in hospitality is not the model. It is the workflow around it: whether revenue managers trust the system, whether it fits how commercial decisions get made, and whether it holds up under the operational pressure of running a hotel portfolio. You have lived that pressure, from the engineeri [... source excerpt omitted ...] as a senior individual contributor with full ownership of client deployments and grow into building the forward deployed engineering team as the hospitality business scales. What You'll Do Own client deployments end to end: scope the engagement, integrate with the client’s PMS, CRS, RMS, and distribution stack, ship the models, and drive adoption inside the revenue organization. Design and ship agentic workflows that revenue managers actually adopt rather than second-guess. Translate deep hotel revenue management practice into decision logic, validating that agent recommendations match the judgment of seasoned revenue managers and directors. Work on-site and remotely with [... source excerpt omitted ...] technical delivery with real commercial domain depth. Strong candidates come from one of two paths, and the best come from both: Engineering side: a senior technical leader with production experience building and deploying machine learning, forecasting, optimization, and agentic AI, ideally in client-facing or embedded delivery roles. Commercial side: experience as a revenue analyst, revenue manager, or revenue director at a large hotel brand, owning real pricing and inventory decisions across multi-property portfolios. Required: Hotel Systems Fluency Demonstrated, hands-on familiarity with the systems hotel revenue teams actually run on, such as: Revenue management systems (