Senior AI Engineer
New
U
UXBERT LabsDigital/UX Design
Riyadh, Riyadh Province, Saudi ArabiaFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 10+ years
- Required Skills
- Node.jsPHPPythonDjangoFastAPIReactLLMLangChain
Requirements
- Bachelor's or Master's degree in Computer Science, Engineering, Artificial Intelligence, or a related field (or equivalent experience).
- Minimum 10+ years of experience in full-stack development.
- Proficiency in frontend (e.g., React) and backend (e.g., PHP, Laravel, Node.js, Python, Django, Flask, FAST API) technologies.
- Working knowledge of leading AI coding platforms and tools, including Claude and OpenAI Cursor.
- Strong expertise in working with Large Language Models (LLMs) such as GPT, BERT, or similar, including fine-tuning, prompting, and integration into applications.
- Hands-on experience with LangChain for chaining LLM calls and LangGraph for building graph-based AI applications.
- Proven ability in cloud platforms (e.g., AWS, Azure, GCP), including services for compute, storage, databases, and AI/ML (e.g., SageMaker, Vertex AI).
- Demonstrated skills in live coding and rapid prototyping.
- Solid understanding of software engineering principles, including version control (Git), CI/CD pipelines, and agile methodologies.
- Excellent problem-solving skills and the ability to work independently or in a team.
Responsibilities
- Design, develop, and deploy full-stack applications that integrate AI models, with a focus on LLMs for tasks such as natural language processing, generation, and automation.
- Collaborate with cross-functional teams to rapidly prototype and iterate on ideas, ensuring quick turnaround from concept to production-ready solutions.
- Utilize LangChain and LangGraph to build efficient, stateful AI agents and multi-step workflows that apply existing models to solve real-world problems.
- Implement cloud-based infrastructure (e.g., AWS, Azure, GCP) for hosting, scaling, and managing AI applications, including data pipelines, APIs, and deployment pipelines.
- Participate in live coding sessions and rapid development sprints to demonstrate and refine solutions in real-time.
- Optimize applications for performance, security, and reliability, ensuring seamless integration of AI components into user-facing systems.
- Troubleshoot and debug complex issues across the stack, from frontend interfaces to backend AI logic and cloud deployments.
- Stay updated on emerging AI tools and best practices to continuously improve development processes and application efficiency.
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