Business Lead AI Engineer

The IT company Andersen is hiring a Business Lead AI Engineer on-site in Abu Dhabi for a project delivering scalable AI solutions for digital transformation. Our customer is a public-sector organization responsible for advancing digital innovation and modernizing services across multiple domains. It supports strategic initiatives in emerging technologies, collaborates with industry and research partners, and develops long-term technology frameworks for improving operational efficiency and service accessibility. The organization focuses on secure, scalable, and sustainable digital development to drive continuous improvement within the broader ecosystem. The project is focused on driving AI initiatives across multiple client engagements within a large-scale digital transformation program in the UAE. It aims to identify opportunities for AI adoption, define effective technical approaches, and deliver scalable AI solutions that support business transformation and innovation.

Responsibilities: - Acting as the primary AI advisor for stakeholders and client representatives. - Identifying business opportunities where AI can create measurable value. - Facilitating workshops and discovery sessions with business stakeholders. - Translating business challenges into technical AI initiatives and delivery roadmaps. - Presenting AI strategies, solution concepts, and implementation approaches to executive and operational audiences. - Participating in pre-sales and solution discussions when required. - Defining AI and GenAI solution architectures. - Evaluating and recommending appropriate AI technologies, frameworks, and platforms. - Establishing AI adoption plans and implementation of roadmaps. - Driving responsible AI practices, governance, and risk mitigation approaches. - Aligning AI initiatives with business goals and measurable outcomes. - Leading AI engineers, ML engineers, and data specialists. - Reviewing architecture decisions and technical designs. - Guiding model development, deployment, and operationalization activities. - Ensuring scalability, maintainability, security, and performance of AI solutions. - Supporting implementation of production-grade AI and GenAI systems. - Serving as a communication bridge between business and technical teams. - Managing expectations across multiple stakeholder groups. - Communicating progress, risks, and recommendations clearly. - Facilitating decision-making processes and resolving ambiguity.

Requirements: - Experience in software engineering, data engineering, machine learning, or AI-related roles for 8+ years. - Experience in a leadership position managing technical teams and client interactions for 3+ years. - Proven experience delivering AI/ML solutions in production environments. - Experience leading customer-facing discussions and solution workshops. - Strong understanding of Machine Learning and Generative AI concepts. - Hands-on experience with LLM-based solutions and modern AI ecosystems. - Experience with frameworks, such as LangChain, LlamaIndex, Semantic Kernel, OpenAI APIs, Azure AI Services, Vector Databases, and RAG architectures. - Experience designing and delivering AI copilots, intelligent assistants, enterprise search solutions, recommendation systems, and NLP solutions. - Experience with at least one major cloud platform: Microsoft Azure (preferred), AWS, or Google Cloud. - Solid understanding of cloud-native architectures, APIs and integrations, security and governance, and AI solution lifecycle. - Strong stakeholder management skills. - Ability to communicate effectively with both technical and non-technical audiences. - Experience facilitating workshops and requirements discovery sessions. - Excellent presentation and storytelling skills. - Strong conflict resolution and consensus-building abilities. - Level of English – from Upper-Intermediate and above.

Nice to have: - Experience as a Solution Architect, AI Architect, or Principal Engineer. - Experience in AI consulting engagements. - Knowledge of Responsible AI and AI governance frameworks. - Experience with MLOps practices and platforms. - Familiarity with data platforms and modern analytics ecosystems. - Experience in regulated industries (banking, healthcare, insurance, telecom, public sector). - Knowledge of agent-based systems and autonomous AI workflows. - Experience with multi-agent architecture. - Public speaking, conference participation, or thought leadership activities. - AI-related certifications from Microsoft, AWS, Google, or equivalent vendors.

Compensation: 3200–6300 EUR per month.