Lead Forward Deployed Engineer, Hospitality
Summary
Lead the end-to-end deployment of an AI revenue platform for hotels, integrating with PMS/CRS/RMS systems and driving adoption among revenue teams.
- 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 client product, engineering, and commercial leadership to integrate cleanly with hotel systems of record and distribution.
- Define the methodology and metrics standards each deployment is held to, ensuring rigor in how performance is framed and measured.
- Represent telos credibly with brand-level revenue and commercial leaders, the EVPs and heads of revenue who buy and rely on this work.
- Build, mentor, and lead the forward deployed engineering team as the function scales.
- 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.
- Revenue management systems (RMS): IDeaS, Duetto, Revenue Analytics, or equivalent, deployed in production at scale.
- Property management systems (PMS): Oracle OPERA or equivalent.
- Central reservation systems (CRS): Amadeus ACRS, Sabre SynXis, or equivalent.
- BI and rate-shopping tools: Lighthouse, STR, Kalibri, Amadeus BI, or equivalent.
- Full command of the hotel revenue management metric set and the methodological distinctions that matter
- Deep lived experience across hotel system engineering or hotel revenue management roles (not back-office IT), pairing senior leadership with hands-on execution.
- Practical experience with major hotel industry APIs such as Oracle Hospitality Integration Platform (OHIP), OpenTravel Alliance (OTA) specs, and Hospitality Technology Next Generation (HTNG) specs.
- Production experience with SQL, Python and modern ML and optimization tooling; comfort across cloud AI services (AWS, Azure, GCP).
- Track record of shipping AI that fits real commercial workflows and earns analyst trust under operational pressure.
- Strong communicator able to move fluently between revenue teams, engineers, and brand-level executives, with a practitioner’s credibility in the room.
- Experience with agentic AI, RAG, Model Context Protocol (MCP), and Universal Commerce Protocol (UCP) architectures.
- Depth in distribution and channel strategy: OTA and wholesale contracting, channel mix and drift, direct-booking optimization.
- Experience with customer insights, loyalty, and segmentation analytics.
- A revenue management certification (e.g., CRME) and continuing industry leadership presence.