Software Engineer, Cloud Infrastructure
Safari AI · Not provided by source
MeritLog read this listing from Safari AI's Greenhouse job board and last checked it on September 27, 2026.
Source: the employer's Greenhouse job board. Open the job post for the latest details.
Job details
- Work model
- Not provided by source
- Salary
- Not listed by source
- Location
- North America
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How this role compares at Safari AI
Safari AI has 7 live roles in MeritLog’s job list across 4 job types, and 3 of them are in engineering. 0 of those jobs list a pay range. That is 0%.
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Job description
About Safari AI Safari AI's vision is to Automate Action of the leading companies in the physical economy, from Entertainment, Live Venues, QSR's, Retail and beyond. The company uses computer vision AI to Measure, Alert and provide AI-generated Recommendations at the operations of leading enterprises such as Merlin/Legoland, 7-11, Tanger Outlets, Charlotte Hornets, Tennessee Titans, and more. Leadership & Culture Safari AI is founded by Ali Vahabzadeh, who has a meaningful exit under his belt and has managed large, high-performing Go To Market and Engineering teams. The company is headquartered in Miami with the Engineering team co-located in Vancouver. About You And How You Succeed At Safari AI You're excited to build a product and invent a market that hasn't existed before. You read documentation first and are not afraid to ask for help when uncertain. You're looking to take ownership/run a singular project and take advantage of the freedom and culture an early stage startup can provide. You are looking to see through the fluff of the modern AI landscape and explore new ways of achieving measurable ROI. Enjoy a small team size ~10, project team of 1-3. What you will be working on regardless the roles • Primary contributor of Safari AI cloud infrastructure • Practice engineering best practices for system design, coding, documentation and communication • Work closely with engineering team members and operation team to identify new priorities and communicate it well • Contribute to engineering development process improvements • Set technical direction for cloud infrastructure stack What you must have • 4-6 years software individual contributor experiences • proficiency in AWS or at least one of the following public cloud: GCP/Azure • proven record on building a complex service from scratch to production • experiences in delivering incremental features and maintaining reliabilities of a production service • good understanding in best practices in software development lifecycle (SDLC) and security compliance Nice-to-Haves • proven experiences of building a team and mentoring skills • streaming processing service experiences • machine learning engineering experiences What we provide • Opportunity to shape an early-stage, mission-driven startup and revolutionize how Enterprises use Computer Vision • Professional growth at a fast-growing, venture-funded start up with a proven founder and leadership team • Competitive salary and meaningful equity for early team members • Unlimited vacation days • Generous health benefits (Health, Vision, Dental) • 401k for US team members • Brand new, top of the line hardware and whatever else you need to help you win We are not considering any agent/agency and only matched candidates will be reached out. !!! Very Important !!! Please send us your code or piece of work, if you are interested in this position and you will not be reached out otherwise. Why bet on Computer Vision and Safari AI? • Huge opportunity hiding in plain sight: leveraging already-installed cameras to automate and real-time action on operational data • Already the market leader in enterprise CV by working with industry leaders with billions in revenue • Large chasm between customer knowledge and market availability, i.e. customers don't know what is available in the market...yet. • Early leader in computer vision; everyone is small and unbranded (i.e. no Amazon or Google in the room to compete with) • Very modular, allowing Safari AI and its customers to invent whole new use cases on a regular basis • Developed the tech and data pipelines over three years and invested several million dollars and is now ready to scale
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