AI Solution Engineer

Company Description Neural Adaptive Learning \& Intelligent Tech Systems (NALITS) Ltd is a UK-based consultancy specialising in AI, data, cybersecurity, and cloud engineering for organisations in complex, highly regulated environments. Founded in 2006, NALITS has nearly two decades of experience delivering production-grade solutions for investment banks, hedge funds, public sector bodies, and large enterprises. The company focuses on secure, scalable, and commercially valuable AI implementations that integrate with existing business processes and technology estates. Its expertise spans AI and machine learning, intelligent process automation, data engineering and analytics platforms, cybersecurity and DevSecOps, and cloud and platform engineering. NALITS’ mission is to build secure, intelligent systems that generate measurable business value and sustainable competitive advantage. https://nalits.com/talent/ai-solution-engineer Role Description The AI Solution Engineer is a full-time hybrid role based in the London Area, United Kingdom, with flexibility for partial work from home. This role involves designing, building, and deploying AI and machine learning solutions that integrate with client data platforms, cloud environments, and existing enterprise systems. Day-to-day responsibilities include translating business requirements into technical architectures, developing prototypes and production-grade models, and collaborating with data engineers, cloud engineers, and cybersecurity specialists to ensure secure and compliant implementations. The AI Solution Engineer will work closely with clients to conduct technical discovery, define solution roadmaps, optimise performance and scalability, and support the transition from proof-of-concept to production. The role also includes documenting solutions, contributing to best practices, and staying current with emerging AI technologies and standards. Qualifications * Ability to translate complex technical concepts into clear, outcome-focused solutions for technical and non-technical stakeholders * Strong skills in AI and machine learning (e.g., model development, evaluation, optimisation, and deployment). * Experience with data engineering and analytics (e.g., data pipelines, ETL/ELT, data modelling, and analytics platforms). * Proficiency in cloud and platform engineering (e.g., AWS, Azure, or GCP, containerisation, and CI/CD workflows). * Understanding of cybersecurity and DevSecOps principles (e.g., secure design, compliance, and threat-aware architectures). * Experience in enterprise integration and modernisation (e.g., APIs, microservices, and integration with legacy systems). * Strong programming skills in relevant languages such as Python, and familiarity with common ML frameworks (e.g., PyTorch, TensorFlow, or similar).