Senior AI Engineer
# Senior AI Engineer **Click Group** · Cairo · `On-site` 🕒 **Статус:** *Опубликовано: 6 дней назад* · *Источник: Indeed* --- ### About the Role Job Summary The Senior AI Developer leads the design, development, and deployment of scalable, production-grade Artificial Intelligence and Machine Learning solutions. Bridging business requirements with cutting-edge AI technologies, this role owns the end-to-end lifecycle of AI applications—including Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), autonomous agentic workflows, and predictive ML models. The Senior AI Developer acts as a technical authority, mentoring software engineers, setting AI engineering standards, and ensuring AI features are performant, secure, cost-effective, and seamlessly integrated into core enterprise software products. Tasks, Duties and Responsibilities AI Solution Architecture & Development - Architect, write, and deploy robust, production-ready AI services and features using LLMs, fine-tuned models, vector databases, and modern AI frameworks (e.g., LangChain, LlamaIndex, AutoGen). - Build and optimize advanced RAG (Retrieval-Augmented Generation) pipelines, semantic search engines, and multi-step agentic systems. - Design, implement, and maintain custom evaluation (Evals) and observability frameworks to continuously measure model output quality, latency, accuracy, and hallucination rates in production. Model Fine-Tuning & Data Engineering - Oversee data preprocessing, feature engineering, vector embedding generation, and dataset curation for training and evaluation pipelines. - Fine-tune open-source models (e.g., Llama, Mistral) and optimize proprietary model prompts/API calls for domain-specific tasks while maintaining low latency and cost efficiency. - Collaborate with data engineering teams to establish secure, high-throughput pipelines for structured and unstructured enterprise data. MLOps, Deployment & Infrastructure - Partner with DevOps/Cloud teams to containerize and deploy AI models and services onto scalable cloud infrastructure (AWS, Azure, or GCP). - Establish CI/CD workflows for AI models, automated prompt versioning, guardrails, and model monitoring tools. - Ensure strict adherence to data privacy, AI security best practices, guardrails, and governance policies (e.g., PII detection, content safety filters). Leadership, Governance & Cross-Functional Alignment - Mentor junior and mid-level software/AI engineers, conducting technical code reviews and sharing best practices in modern AI development. - Collaborate closely with Product Managers and Solution Architects to translate business cases into technical requirements and feasibility studies. - Evaluate emerging AI research, open-source frameworks, and commercial APIs to recommend state-of-the-art tools for company platforms. Job RequirementsEducation & Experience - Education: Bachelor’s degree in Computer Science, Software Engineering, Artificial Intelligence, Data Science, or a related technical field (Master's degree preferred). - Overall Experience: 6 to 10+ years of professional software engineering experience, with 3 to 5+ years specifically focused on building, deploying, and maintaining production AI/ML applications. - Track Record: Proven history of taking AI features from concept to production at scale, owning architectural decisions and model evaluation pipelines. Technical Knowledge & Skills - Programming Languages: Mastery of Python; proficiency in TypeScript/JavaScript, C++, or Go is a plus. - AI/LLM Frameworks: Deep experience with frameworks like LangChain, LlamaIndex, Haystack, AutoGen, and Hugging Face Transformers. - Machine Learning & Deep Learning: Proficiency with PyTorch, TensorFlow, or Scikit-Learn. - Data & Vector Databases: Experience with vector stores (e.g., Pinecone, Qdrant, Milvus, pgvector) and relational/non-relational databases. - Cloud & MLOps: Hands-on experience with AWS (SageMaker, Bedrock), Azure AI Services, GCP (Vertex AI), Docker, Kubernetes, and API gateway deployment. - Software Engineering Fundamentals: Strong background in REST/gRPC API design, microservices architecture, async processing, and system design. Preferred Certifications (Any of the following are a plus) - Cloud AI Certifications: AWS Certified AI Practitioner / ML Specialty, Azure AI Engineer Associate, or Google Cloud Professional ML Engineer. - Deep Learning Certifications: DeepLearning.AI or NVIDIA Certified Associate. Pay: E£1.00 per month Work Location: In person
Наблюдалась 2026-10-06, впервые 2026-09-30, источник — Indeed.