Senior AI Engineer
RemoteSaudi Arabia
Job Summary
Design and deploy full-stack applications integrating large language models for natural language processing, generation, and automation. Collaborate with cross-functional teams to rapidly prototype and iterate on ideas, utilizing LangChain and LangGraph to build efficient, stateful AI agents and multi-step workflows. Implement cloud-based infrastructure on AWS, Azure, or GCP for hosting, scaling, and managing AI applications, including data pipelines and deployment pipelines. Optimize applications for performance, security, and reliability while troubleshooting complex issues across the stack. Participate in live coding sessions and rapid development sprints to demonstrate and refine solutions in real-time.
Required Qualifications
- 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 and Laravel, Node.js, Python, Django, Flask, FAST API) technologies
- Working knowledge of leading AI coding platforms and tools, including Claude, OpenAI Cursor, and similar frameworks for building and integrating AI-driven applications
- 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 to quickly validate and implement ideas
- 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 to deliver high-quality results under tight deadlines
Desired Qualifications
- Experience with additional AI frameworks like Hugging Face Transformers, TensorFlow, or PyTorch
- Knowledge of containerization (Docker) and orchestration (Kubernetes) for deploying AI applications at scale
- Familiarity with data engineering tools (e.g., Apache Airflow, Spark) for handling AI data pipelines
- Background in DevOps practices to automate infrastructure and deployment processes
- Strong communication skills to explain technical concepts to non-technical stakeholders
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