Senior Full Stack AI Engineer

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🔥 40 minutes ago

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Spoon

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2019

💼 Consulting

🏥 Healthcare

👥 HR Tech

Consulting • Healthcare • HR Tech

Spoon is a recruitment agency that specializes in connecting businesses with top remote talent from Latin America and the Philippines. The company streamlines the hiring process for various roles, including tech, healthcare, finance, and customer service, while helping organizations save on costs associated with domestic hiring. Spoon manages every aspect of recruitment from candidate sourcing to onboarding, ensuring that businesses can scale efficiently without compromising on quality.

📋 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.