Lead AI Engineer

Lead AI Engineer | Sovereign Tax Intelligence PlatformQuantumFy Group | Dubai/UAE (hybrid) | Full-timeCompany Description QuantumFy Group is an AI orchestration and execution company focused on highly regulated industries such as banking, energy, defence, healthcare, government, and digital assets. The company builds an intelligence layer on top of existing systems, integrating with platforms like SCADA, core banking, ERP, CMMS, and clinical systems to improve operational outcomes rather than replace infrastructure. Its AI Operating System runs a closed decision loop Predict, Decide, Act, Verify with explainability, auditability, and human-in-the-loop governance embedded from the start to meet strict regulatory standards. QuantumFy Group operates with 100+ engineers across eight countries, with regional headquarters in Dubai and Riyadh and deep compliance expertise across EU and GCC regulatory frameworks. Trusted by central banks, Tier‑1 financial institutions, sovereign programs, and energy majors, the company measures success in real operational impact and accountable delivery.The program. QuantumFy Group is building a national-scale, AI-enabled tax intelligence and orchestration platform for a European government authority. The platform connects existing systems rather than replacing them: it consolidates fragmented data into a sovereign data foundation, resolves entities into a living taxpayer graph, detects patterns isolated systems cannot see, scores risk with outcome feedback, and converts approved recommendations into owned, auditable activity. Material decisions remain human-approved at all times. This is government AI done properly: explainable, secure, governed, phase-gated by evidence.The role. You own the technical delivery of the platform end to end. You will design and lead the build of the data foundation and integration layer across legacy government systems; the entity resolution and graph analytics capability; ML risk-scoring models with drift monitoring and outcome feedback loops; LLM and RAG components for case intelligence, with guardrails fit for a national authority; and the orchestration and audit layer that makes every recommendation traceable. You lead a senior squad, set the engineering standards, and represent the technical solution in front of a demanding institutional client alongside our leadership.What you bring. 8+ years of production engineering with deep Python; distributed data platforms (Spark, Kafka or equivalents); graph databases and entity-resolution at scale; applied ML in production (risk scoring, anomaly detection) and modern LLM/RAG architecture; Kubernetes and hybrid cloud/on-premise deployment, including sovereign or air-gapped environments; a security and privacy mindset fluent in GDPR and the EU AI Act; and the seniority to lead engineers and stand in front of a government steering committee. Experience in tax, financial crime, fraud, or other regulated-data domains is a strong advantage. English fluent; Hungarian a plus.What we offer. Top-tier compensation, a leadership seat on a program of genuine national significance, a modular vendor-independent architecture you will shape from the first line, and a company of 100+ engineers across eight countries delivering for central banks, energy majors, sovereign programs, and healthcare systems.Apply at quantumfygroup.com or contact Margit Gulyas directly on LinkedIn, mg@quantumfygroup.comQualificationsStrong foundation in Computer Science, with expertise in Software Development and designing scalable, secure, and maintainable systems.Advanced skills in Neural Networks and Pattern Recognition, including experience building and deploying deep learning models in production.Hands-on experience with Natural Language Processing (NLP), particularly in developing explainable, auditable models for regulated environments.Proficiency in modern programming languages and frameworks commonly used for AI engineering (e.g., Python, Java/Scala, PyTorch, TensorFlow, and distributed computing frameworks).Experience with MLOps practices, including CI/CD for ML, containerization (Docker, Kubernetes), model monitoring, and lifecycle management.Background in designing AI systems that comply with regulatory and security requirements; familiarity with standards relevant to financial services, energy, healthcare, or government is an advantage.Demonstrated ability to lead cross-functional technical teams, mentor engineers, and