AI Product Engineer / AI Core Engineer

About the Role We are looking for an AI Product Engineer / AI Core Engineer who can design, build and improve AI-powered product features. The ideal candidate should be comfortable working across large language models, recommendation systems, computer vision, structured outputs, open-weight models and AI integrations. This role requires someone who can move from product requirement to technical solution, prototype quickly and convert experiments into reliable production systems. Key Responsibilities Design and develop AI-powered product features. Work with LLMs, prompt engineering and commercial AI APIs. Build recommendation, classification, ranking and personalisation workflows. Develop computer vision features for image understanding, tagging and classification. Create structured and reliable AI outputs in JSON or application-ready formats. Evaluate and integrate open-source and open-weight models. Compare models based on quality, speed, cost, privacy and deployment requirements. Build retrieval, embeddings and vector-search workflows. Design short-term and long-term memory layers where required. Create evaluation frameworks to test accuracy, consistency, latency and reliability. Improve prompts, model pipelines and AI workflows through continuous testing. Optimise model performance, inference speed and API costs. Build fallback and error-handling mechanisms for unreliable AI outputs. Collaborate with product, backend, mobile and design teams. Convert business requirements into practical AI architecture. Maintain clean, reusable and production-ready Python code. Document models, prompts, experiments, datasets and technical decisions. Use GitHub or GitLab for version control, branching, code reviews and collaboration. Support deployment, monitoring, debugging and maintenance of AI services. Required Skills Strong understanding of AI and machine learning concepts. Hands-on experience with Python. Experience working with LLMs, prompt engineering and AI APIs. Knowledge of embeddings, vector search, classification or recommendation systems. Understanding of computer vision and image-processing concepts. Ability to generate and validate structured AI outputs. Experience building end-to-end AI workflows, not only single API calls. Understanding of model evaluation, hallucination control and reliability. Experience with Git repositories and collaborative development workflows. Strong problem-solving and analytical ability. Ability to work independently and take technical ownership. Good communication and documentation skills. Preferred Skills Experience with OpenAI, Claude, Gemini or similar APIs. Experience with LangChain, LlamaIndex or custom orchestration frameworks. Familiarity with vector databases such as Pinecone, Qdrant, Weaviate, FAISS or pgvector. Experience with PyTorch, TensorFlow or Hugging Face. Experience working with open-weight models and local inference. Knowledge of fine-tuning, LoRA, quantisation or model optimisation. Experience with recommendation engines, RAG, memory layers or multimodal AI. Familiarity with Docker, APIs, cloud deployment and MLOps. Experience building AI features for consumer-facing applications. What We Are Looking For We are looking for someone who: Is technically strong and practical. Can research, test and compare multiple approaches before implementation. Understands when to use APIs, open-weight models, deterministic logic or hybrid systems. Works quickly without compromising reliability. Uses AI-native tools to improve development speed, testing and documentation. Can independently solve problems and communicate technical risks early. Is comfortable working in a fast-moving startup environment. Takes ownership from prototype to production. How to Apply Send your CV to contact@cyurae.com along with: GitHub or GitLab profile. Links to relevant AI or machine learning projects. A brief explanation of one AI system you built. Current location. Current and expected compensation. Notice period or earliest joining date. .