AI Software Developer

Company Description Wafi Engineering is an engineering and technology firm delivering advanced industrial solutions across aerospace, digital systems, infrastructure, and manufacturing. The company’s aerospace vertical focuses on generative design, carbon composite UAV manufacturing, CFD simulations, and HIL testing aligned with FAA and military standards. Its digital arm builds full stack SaaS architectures, custom ERP systems, web applications, and automated PyTorch AI data pipelines using React and AWS. Wafi Infrastructure designs solar-integrated infrastructure projects, while the manufacturing wing produces CNC‑machined BLDC motor fans and surgical equipment. This multidisciplinary environment offers opportunities to work on complex, real‑world engineering challenges with cutting‑edge tools and technologies. Role Description The AI Software Developer will design, build, and deploy AI-powered software solutions that support Wafi Engineering’s aerospace, digital, infrastructure, and manufacturing projects. Day-to-day responsibilities include developing and maintaining production-grade AI systems, implementing and optimizing neural network models, and integrating pattern recognition and NLP capabilities into existing and new applications. The role involves collaborating with cross-functional engineering and product teams to translate business and technical requirements into scalable software, conducting experiments, evaluating model performance, and refining models for robustness and efficiency. The developer will also contribute to code reviews, documentation, and continuous improvement of development practices and pipelines. This is a full-time, hybrid role based in the London Area, United Kingdom, with flexibility for some work from home. Qualifications - Strong foundation in Computer Science and Software Development, including data structures, algorithms, and modern software engineering practices. - Hands-on experience with Neural Networks and Pattern Recognition, including training, tuning, and deploying models to production environments. - Practical knowledge of Natural Language Processing (NLP), such as text classification, information extraction, and conversational interfaces. - Proficiency in Python and one or more deep learning frameworks (e.g., PyTorch, TensorFlow), plus experience with REST APIs and cloud platforms (e.g., AWS, Azure, GCP). - Experience with data pipelines, version control (Git), testing frameworks, and CI/CD tools for AI/ML applications. - Bachelor’s or master’s degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent practical experience. - Ability to work effectively in a hybrid environment, communicate clearly with multidisciplinary teams, and manage priorities in a fast-paced setting. - Familiarity with applications in aerospace, industrial automation, or embedded systems is a plus.