Endava Software Architect (Data & AI) \\\| SmartRecruiters Google Chrome Microsoft Edge Apple Safari Mozilla Firefox . Software Architect (Data & AI) Full-time Company Description Technology is our how. And people are our why. For over two decades, we have been harnessing technology to drive meaningful change. By combining world-class engineering, industry expertise and a people-centric mindset, we consult and partner with leading brands from various industries to create dynamic platforms and intelligent digital experiences that drive innovation and transform businesses. From prototype to real-world impact - be part of a global shift by doing work that matters. Job Description Architects design digital blueprints for client projects. They create scalable, efficient, and secure IT systems to ensure alignment with business goals before, during, and after development. Our Architects possess a blend of technical expertise, strategic vision, and strong communication skills. As a Software Architect (Data & AI) at Endava you will design and lead enterprise-scale data and AI solutions. You will bridge business and technology, ensuring that data platforms and AI systems are secure, scalable, ethical, and business-aligned. In this role, youll shape how data and AI drive value across the organizations. Responsibilities: Design end-to-end data and AI architectures, covering data pipelines, storage, analytics, and ML/AI platforms. Define and implement data strategies that ensure scalability, performance, and compliance. Use technologies to solve complex business challenges. Integrate AI/ML models into enterprise systems, with focus on trust, transparency, and explainability. Establish governance frameworks for data quality, security, and AI ethics. Support the teams hands-on work if required. Advise and collaborate with stakeholders across the organization. Mentor teams and promote innovation. Qualifications 15+ years in software development, 3 + years of experience in architecture role. Strong background in cloud platforms (AWS, Azure, GCP). Knowledge of ML/AI platforms, MLOps, data engineering, and model deployment. Solid understanding of DevOps and DataOps principles Experience with modern ways of working, including AI augmented. Excellent communication and leadership skills. Degree in Computer Science, Data Science, or related field. Would be a plus: Experience in regulated industries (e.g., banking, healthcare, insurance). Understanding of AI ethics, governance, and regulatory frameworks. Strategic mindset with the ability to balance technical and business priorities. Additional Information Discover some of the global benefits that empower our people to become the best version of themselves: Finance: Competitive salary package, share plan, company performance bonuses, referral bonus. Career Development: Career coaching, global career opportunities, non-linear career paths, internal development programmes for management and technical leadership. Learning Opportunities: Complex projects, rotations, internal tech communities, training, certifications, coaching, online learning platforms subscriptions, pass-it-on sessions, workshops, conferences. Work-Life Balance: Hybrid work and flexible working hours, employee assistance programme. Health: Global internal wellbeing programme, access to wellbeing apps. Community: Global internal tech communities, hobby clubs and interest groups, inclusion and diversity programmes, events and celebrations. At Endava, were committed to creating an open, inclusive, and respectful environment where everyone feels safe, valued, and empowered to be their best. We welcome applications from people of all backgrounds, experiences, and perspectivesbecause we know that inclusive teams help us deliver smarter, more innovative solutions for our customers. Hiring decisions are based on merit, skills, qualifications, and potential. If you need adjustments or support during the recruitment process, please let us know. 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The role requires over 15 years in software development with at least 3 years in an architecture role. A strong background in cloud platforms such as AWS, Azure, and GCP is necessary. Candidates must possess knowledge of ML/AI platforms, MLOps, data engineering, and model deployment, along with a solid understanding of DevOps and DataOps principles. Experience with modern ways of working, including AI augmented approaches, is also required. A degree in Computer Science, Data Science, or a related field is a prerequisite.