Senior Full Stack AI Engineer

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🔥 2 hours ago

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Spoon

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2019

🎯 Recruiter

👥 HR Tech

🤝 B2B

Recruitment • HR Tech • B2B

Spoon is not described in the supplied content. The provided text appears to be for a different company (Walter), which operates a remote staffing/recruitment service that connects businesses with talent in Latin America and the Philippines. Walter handles sourcing, screening, interviews, onboarding and ongoing support, offers a 12-month replacement guarantee, and targets roles such as developers, customer service reps, sales reps and back-office positions. The service is marketed to businesses seeking cost-efficient remote hires and emphasizes saving up to ~80% compared to North American salaries.

📋 Description

• Build end-to-end applications that incorporate generative AI capabilities into real user workflows • Develop scalable backend services, APIs, and integrations using modern engineering practices • Build responsive and maintainable frontend experiences using modern frameworks • Design modular system architectures that support scalability, reliability, and long-term maintainability • Integrate LLMs and other AI tools into production applications with appropriate safeguards and monitoring • Optimize prompt flows, data pipelines, and system interactions for consistency and performance • Translate business requirements into technical solutions and make strong implementation trade-offs • Own features from ideation through development, testing, deployment, and iteration • Reuse and adapt proven solutions where appropriate to accelerate delivery • Continuously improve product quality based on performance data, feedback, and operational learnings

🎯 Requirements

• Strong full stack engineering experience, ideally 5+ years • Proficiency in backend development with technologies such as Node.js, Python, or similar • Strong frontend experience with frameworks such as React or comparable modern tools • Experience building and consuming APIs, working with databases, and deploying on cloud platforms • Hands-on experience integrating generative AI into production applications • Practical understanding of prompt engineering and AI system limitations, including failure modes and edge cases • Proven ability to design systems that scale beyond MVP and remain maintainable over time • Strong understanding of software architecture, system design, and engineering best practices • Demonstrated experience shipping multiple production-grade products or platforms • Ability to combine traditional software engineering discipline with modern AI-driven workflows • Experience working independently with strong ownership and product mindset.