Software & AI Manager

Job Summary We seek an experienced and forward-thinking Software & AI Manager to lead the design, development, and deployment of high-impact software and AI-driven solutions. This role requires a blend of hands-on technical leadership, strategic architecture oversight, and people management, driving excellence across the full software lifecycle while embedding AI/ML capabilities into core products and platforms. Key Responsibilities Software Engineering Leadership • Establish and maintain robust processes and documentation across the Software Product Lifecycle, from inception to retirement. • Oversee the end-to-end application lifecycle—including requirements analysis, system design, development, testing, deployment, release, and post-launch support. • Take ownership of critical technical components: UI/UX design, business logic, data access layers, external API integrations, and database schema design. • Evaluate and recommend tools, frameworks, and methodologies to ensure product quality, scalability, and maintainability. • Deliver production-ready software by writing clean, efficient, and well-documented code. • Mentor and coach engineering teams in: Writing comprehensive unit and UI tests, troubleshooting, debugging, and performance optimisation, designing intuitive user interfaces and developing real-time and batch data processing systems • Collaborate with Sales, Product, and Project teams to scope, prioritise, and deliver new features. • Ensure both new and legacy systems adhere to quality, security, and compliance standards. • Proactively research and propose new software products, tools, and architectural improvements. • Maintain thorough technical documentation for sustainability and knowledge transfer. • Keep abreast of emerging technologies and industry best practices. • Recruit top talent and design individualised training and career development plans. AI/ML Strategy & Execution • Design, develop, and optimise AI models, leveraging both open-source and proprietary resources. • Build scalable AI solutions using cloud platforms (AWS/Azure/GCP), data pipelines, and modern databases. • Implement and deploy NLP, LLMs, and other AI frameworks for real-world use cases. • Architect and deliver RESTful APIs to expose AI capabilities to internal/external systems. • Apply Retrieval-Augmented Generation (RAG) to improve relevance, accuracy, and trustworthiness of AI outputs. • Practise advanced prompt engineering, including instruction tuning, templating, and fine-tuning strategies. • Embed AI development within CI/CD pipelines, enforcing test-driven development and reproducible workflows. • Conduct rigorous evaluation of models using appropriate metrics, benchmarks, and validation protocols. • Continuously monitor advancements in AI/ML research and translate them into business value. • Partner with stakeholders to convert business challenges into AI-powered solutions. • Ensure seamless integration of AI components with existing software ecosystems. Requirements Experience & Technical Background • Bachelor’s degree in Computer Science, Engineering, or a related field (Master’s preferred). • 10+ years of hands-on software development and leadership experience. • Proven track record as a Team Lead or Tech Lead, managing end-to-end software projects. • Strong domain experience in cybersecurity (especially European standards), IP telephony, and data networking, ideally in a project or technical management capacity. • Demonstrated portfolio of released mobile/web applications (App Store, Play Store, or enterprise deployments). • Proficiency in multiple programming languages: Essential: SQL, Python, Strongly preferred: Node.js, TypeScript, C#, JavaMobile: Swift, Objective-C, Java (Android), plus hybrid frameworks (e.g., React Native, Flutter) • Expertise in: SDLC & Agile methodologies, data modelling, and relational (RDBMS) & NoSQL database design, REST/SOAP API integration, Cloud-based AI/ML deployment (AWS/Azure/GCP) (a plus), ML frameworks (TensorFlow, PyTorch) (a plus) AI/ML Competencies • Solid foundation in machine learning (supervised/unsupervised learning, neural networks, optimisation, evaluation metrics). • Experience with data preprocessing, feature engineering, and SQL for AI pipelines. • Deep understanding of algorithms, data structures, and their role in scalable ML systems. • Familiarity with MLOps practices, including CI/CD for AI, model versioning, and monitoring. Soft Skills & Attributes • Exceptional verbal and written communication, able to explain technical concepts to non-technical audiences. • Strong organisational, multitasking, and prioritisation skills. • Self-motivated, independent, and able to thrive with minimal supervision. • Collaborative team player who can inspire, mentor, and align engineers toward shared goals. • Adaptable under pressure, with a bias for action in fast-paced environments. • Committed to lifelong learning and technology innovation. • Willingness to travel as required.