обновлено 7 дней назад
Full-Stack AI Engineer (LLMs, AI Products & Full-Stack Development)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Full-Stack AI Engineer (LLMs, AI Products & Full-Stack Development): Build and deploy production-ready AI-powered applications across full-stack systems, AI pipelines, APIs, vector databases, and cloud infrastructure with an accent on LLM integration, RAG pipelines, and scalable product delivery. Focus on designing inference APIs, developing responsive AI applications, orchestrating data workflows, and optimizing reliability, security, latency, and cost.
Location: Remote in Argentina, Peru, Brazil, Colombia, or Mexico. Working hours: U.S. Business Hours
Company
is hiring for a client building and deploying production-ready AI-powered applications.
What you will do
- Build and deploy AI-powered applications, assistants, chatbots, copilots, and intelligent workflows using LLM and AI frameworks.
- Develop inference APIs, backend services, microservices, and frontend applications that integrate AI with business logic.
- Implement embeddings, vector search, RAG pipelines, and semantic retrieval with vector databases.
- Build ETL/ELT pipelines and AI data workflows using workflow orchestration tools and cloud data platforms.
- Deploy and operate applications with Docker, Kubernetes, and CI/CD pipelines while monitoring uptime, latency, reliability, scalability, and cost.
- Implement authentication, permissions, API protection, security and privacy controls, and document system and deployment workflows.
Requirements
- 3+ years of software engineering experience integrating AI/ML.
- Strong Python and JavaScript/TypeScript skills.
- Experience with PyTorch, TensorFlow, or similar AI frameworks and deploying AI or LLM applications into production.
- Strong frontend experience with React, Next.js, Vue, or similar frameworks.
- Experience with APIs, vector databases, embeddings, RAG pipelines, SQL, and cloud platforms.
- Familiarity with Docker, Kubernetes, and CI/CD workflows.
Nice to have
- Experience building AI-powered SaaS products.
- Experience with LangChain, AI agents, Vertex AI, SageMaker, Kubeflow, or MLflow.
- Experience with LLM fine-tuning, MLOps, microservices, serverless architectures, or startup and high-growth product environments.
Culture & Benefits
- Full-time remote work from the listed countries.
- Cross-functional collaboration with product managers, engineers, and data teams.
- Work focused on reliable, scalable, secure AI systems and measurable business value.
Hiring process
- Initial recruiter screening and video interview with a recruiter.
- Technical assessment followed by a client interview.
- Offer and onboarding; applicants also receive a Spark Hire invitation to record an introductory video.
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