Think about your last hotel stay. Did you skip the front desk line with mobile check-in? Message the staff for extra pillows? Order a late-night snack with a tap on your phone? Then you’ve likely run into Canary in the wild.
Canary Technologies is the leading agentic AI platform for hotel and guest management, powering the digital infrastructure for more than 20,000 hotels in 125+ countries. The world's most renowned hospitality brands, including Marriott International, Four Seasons and Wyndham Hotels & Resorts, partner with us to increase revenue, improve operations and elevate the guest experience.
We’ve executed the largest deployment of autonomous AI systems in hospitality, building technology that fundamentally redefines how guests and hotels interact. It’s made us one of the top-funded hotel technology companies in the world, with nearly $200M raised to date.
Canary has been recognized as a 2024 and 2025 Deloitte Technology Fast 500™ company, Inc. 5000 fastest-growing company, and swept the 2026 HotelTechAwards, including Best Place to Work, #1 Guest Experience Platform, and the Hotelier’s Choice Award. We’re scaling our team to bring innovation to life faster than ever.
We're growing quickly, and we're looking for people who are passionate about their work, want to grow with us and are ready to take on more responsibility along the way. We value rigor and velocity in equal measure: high standards, fast pace, real ownership. If that's the environment you're looking for, this is the place for you.
Come join us! Let’s shape the future of hospitality together.
Canary Technologies is hiring a Sales Engineer to partner closely with Sales, Product, and Customer Success to drive technical validation and value articulation throughout the sales cycle. This role will own demos, technical discovery, solution design, and assist/ coordinate RFP and RFI responses, ensuring accuracy, differentiation, and alignment with buyer requirements. The ideal candidate is technically fluent, commercially sharp, and comfortable operating in an early-stage, high-ownership environment. Prior experience supporting B2B SaaS sales teams, is strongly preferred.
What You’ll Do
- Establish and execute standard demo workflows, including customization patterns and coverage for newly launched features
- Define and document technical discovery SOPs to consistently map customer systems, integrations, data flows, and constraints
- Create repeatable solution design frameworks and proof plans in partnership with Engineering and Product
- Build and maintain standardized RFP/RFI response processes, including accurate, differentiated technical content and internal coordination
- Develop processes to validate early-stage product features, capture field feedback, and prepare them for sales enablement
- Partner with Sales to formalize deal execution playbooks covering objection handling, stakeholder alignment, and proof milestones
- Document and maintain security and compliance artifacts to support buyer reviews and risk assessments
- Produce scalable enablement assets, including playbooks, guides, and reusable demo components
What We’re Looking For
- Experience: 3–5+ years in a Sales Engineering role supporting B2B SaaS sales
- Domain exposure: Familiarity with hospitality systems (PMS preferred) or similarly complex integration environments
- Technical fluency: Working knowledge of APIs (REST, webhooks) and light scripting to support demos and proofs
- Security/compliance: Experience supporting security, privacy, and compliance reviews with enterprise buyers
- RFP/RFI: Proven experience owning or significantly contributing to technical RFP/RFI responses
- Early-stage product: Demonstrated ability to validate v0/v1 features and convert field feedback into sales enablement
- Sales partnership: Track record of effective technical discovery, objection handling, and stakeholder alignment
- Communication: Clear, concise, executive-level written and verbal communication
- Ownership mindset: Comfortable operating autonomously in fast-moving, ambiguous environments with an outcome-driven mindset
Compensation
Target cash compensation ranges from $150,000 - $190,000, including a fixed annual salary and uncapped commission paid monthly.
This role also includes a stock option grant, subject to board approval.
Actual compensation will be commensurate with the candidate's skill level, experience, and specific work location.
We work hard to make Canary a fun, rewarding, and high-energy place to work. Here’s how we take care of our flock:
Time Off
- Unlimited PTO: Take the time you need to truly rest and recharge.
- Holidays + Canary Days: Standard holidays plus monthly company-wide days off for a guaranteed long weekend.
- Birthday Holiday: A dedicated day off to celebrate you!
Travel & Office Flexibility
- Office Exchange: A travel stipend to visit the team in person at our SF, NY, or Dallas hubs.
- Canary Hotel Experience: Staying at a Canary hotel? We’ve got you covered with a credit toward your stay.
- Preferred Hotels Discount: Enjoy a minimum 30% off the best available rate at select partner hotels globally.
Growth & Community
- Self Improvement Club: A monthly budget to help you smash your personal goals.
- Professional Development: Level up your career with a dedicated learning stipend to fuel your skills and cross-functional connection.
- Referral Program: Help us grow the flock and score a cash bonus for successful hires.
Canary Technologies New York, New York, USA Office
575 8th Ave, New York, NY, United States
Similar Jobs
What you need to know about the NYC Tech Scene
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory
