Full Stack AI Engineer (Production-Grade Systems)

🌟 We’re Hiring: Full Stack AI Engineer (Production-Grade Systems)📍 Location: United Arab Emirates (Remote)🕒 Employment Type: Part-Time💼 Experience Level: Mid-Level to Senior🌐 Work Arrangement: Fully RemoteAbout UsWe are a technology-focused organization building intelligent digital products that combine artificial intelligence, modern software engineering, cloud infrastructure, and data-driven automation. Our teams develop reliable systems designed for real-world production environments, with a strong focus on scalability, security, performance, and user experience.We value engineering excellence, experimentation, ownership, and practical innovation. We are looking for a hands-on engineer who can turn AI concepts into robust, maintainable products.The RoleWe are seeking an experienced Full Stack AI Engineer (Production-Grade Systems) to design, build, deploy, and maintain AI-powered applications across the frontend, backend, data, and infrastructure layers.The ideal candidate is comfortable moving from model and API integration to database design, backend services, user interfaces, cloud deployment, monitoring, and production troubleshooting.Key ResponsibilitiesDesign and develop scalable full-stack applications incorporating AI and machine-learning capabilities.Build production-ready frontend applications using modern JavaScript/TypeScript frameworks.Develop reliable backend services, APIs, microservices, and integrations using Python, Node.js, or comparable technologies.Integrate large language models, machine-learning APIs, embeddings, vector databases, RAG pipelines, and AI agents into production applications.Design data flows and application architectures that support reliable AI inference and business workflows.Develop RESTful APIs and event-driven services with appropriate authentication, authorization, validation, logging, and error handling.Design and maintain relational and NoSQL databases, data models, indexes, and efficient queries.Implement AI evaluation, prompt-management, model-selection, monitoring, and quality-control processes.Build retrieval-augmented generation systems using appropriate embedding, retrieval, ranking, and context-management techniques.Integrate third-party APIs, SaaS platforms, payment systems, identity providers, analytics tools, and enterprise services.Develop asynchronous jobs, queues, background workers, scheduled processes, and event-driven workflows.Build automated testing across unit, integration, API, frontend, and end-to-end layers.Implement CI/CD pipelines for reliable software delivery and controlled production releases.Deploy and operate applications using cloud platforms, containers, orchestration tools, and infrastructure-as-code where appropriate.Monitor application performance, availability, latency, resource utilization, AI quality, and operational health.Diagnose production incidents and implement permanent fixes rather than temporary workarounds.Optimize application performance, database queries, API latency, cloud costs, and AI inference efficiency.Implement secure handling of credentials, customer information, API keys, model inputs, outputs, and sensitive data.Apply appropriate safeguards against prompt injection, data leakage, unauthorized access, insecure dependencies, and other AI-specific risks.Collaborate with product managers, designers, data professionals, security teams, and business stakeholders to translate requirements into technical solutions.Participate in architecture reviews and make pragmatic technology decisions based on reliability, scalability, maintainability, and cost.Write clear technical documentation covering architecture, APIs, deployment procedures, operational processes, and system dependencies.Review code, establish engineering standards, and contribute to development best practices.Research emerging AI technologies and evaluate their practical value for production applications.Maintain technical debt responsibly and continuously improve system architecture and developer experience.Support incident response, root-cause analysis, release management, and production maintenance.Ensure systems meet relevant security, privacy, compliance, and data-governance requirements.Take ownership of features from technical design through implementation, deployment, monitoring, and continuous improvement.RequirementsBachelor’s degree or equivalent qualification in Computer Science, Software Engineering, Artificial Intelligence, Data Science, or a related field is preferred.3+ years of professional software-engineering experience, with practical experience delivering production applications, is preferred.Strong proficiency in Python, TypeScript/JavaScript, or comparable programming languages.Hands-on experience with modern frontend frameworks such as React, Next.js, Vue, or equivalent.Strong backend development experience using FastAPI, Django, Node.js, NestJS, Express, or comparable frameworks.Solid understanding of REST APIs, authentication, authorization, databases, caching, queues, asynchronous processing, and distributed systems.Practical experience integrating LLMs, AI APIs, embeddings, vector databases, RAG, agents, or machine-learning services.Experience with PostgreSQL or other relational databases plus familiarity with NoSQL technologies.Experience with Git, automated testing, CI/CD, Docker, and cloud deployment.Familiarity with AWS, Azure, Google Cloud, or comparable cloud platforms.Experience with observability tools, logging, monitoring, metrics, tracing, and production troubleshooting.Strong understanding of software architecture, API security, application performance, and scalable system design.Knowledge of AI safety, prompt-injection mitigation, data privacy, model evaluation, and responsible AI practices is advantageous.Experience with Kubernetes, Terraform, serverless architectures, message brokers, or infrastructure-as-code is advantageous.Strong analytical, debugging, problem-solving, and technical communication skills.Ability to work independently in a remote environment while collaborating effectively with distributed teams.Relevant cloud, software-engineering, AI, or security certifications are advantageous but not required.What We OfferFlexible part-time working opportunities within a technology-driven and AI-focused environment.Competitive compensation aligned with experience, engineering expertise, and production responsibilities.Opportunity to build real-world AI products spanning frontend, backend, data, cloud infrastructure, and intelligent automation.Exposure to modern LLMs, AI agents, RAG architectures, cloud platforms, developer tooling, observability, and scalable software systems.Professional development opportunities and continuous learning in artificial intelligence, software architecture, cloud engineering, cybersecurity, and emerging technologies.A highly collaborative and engineering-focused environment where ownership, experimentation, reliability, security, and technical excellence are valued.