Data Architect
Role details
Job location
Tech stack
Job description
You will be joining a confidential, high-priority project involving the design and delivery of a sophisticated AI platform built around computer vision, multimodal reasoning, forensic image analysis, and hybrid edge-cloud inference. The platform will be trained on a proprietary dataset of over 500,000 labelled real-world images and must operate reliably across both online and offline environments.
The project is structured across five interconnected AI modules, each requiring primary models, fallback strategies and EU-hosted alternatives. It integrates with enterprise CRM infrastructure and is designed for full production deployment within 12 months.
A preliminary technology selection has been made as a starting point. It includes SAM 2, YOLO11-seg, LLaVA-Next, DINOv2, LoFTR, Stereo-IMU, Depth Pro, Milvus, and EU-hosted alternatives via Regolo.ai. This selection represents our best current thinking - not a locked specification. The AI landscape is moving fast enough that some of these choices may be superseded by better tools before or during the build. We expect the Lead AI Architect to treat this stack as a hypothesis, validate it rigorously, and replace any component where a superior alternative exists at the time of implementation.
The complexity is real. The timeline is fixed. The dataset is substantial. The stakes are high.
The Role
As Lead AI Architect, you are responsible for the overall technical architecture, model orchestration, and delivery integrity of the platform. You will make the critical decisions - on model selection, edge vs cloud inference, data pipeline design, fallback strategies, and EU compliance - and you will own the consequences of those decisions through to production.
You will lead a hybrid team of five senior engineers and various specialised AI agents that will be created in the initial phase of the project to assist the team.
You will also serve as the primary liaison with an academic research partner responsible for the R&D and certification of one of the platform's core security modules.
Beyond the technical, you are the person who holds the team together. You create the conditions for constructive disagreement, mutual accountability, and honest communication. You are comfortable having difficult conversations and skilled at bringing people to a conclusion without leaving casualties. You are the "enabler", not the "boss".
This is not a role for someone who has only worked in research, or only in engineering. You need to have done both - published work and shipped systems. You understand that in a fast-moving AI landscape, the right architecture today may need to be partially rebuilt in six months, and you plan accordingly.
What You Will Be Responsible For
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Reviewing, validating and where necessary replacing the preliminary technology selection based on the state of the AI landscape at the time of implementation
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Designing and owning end-to-end technical architecture across five AI modules and two operational applications
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Orchestrating the full model stack across vision, multimodal reasoning, forensic analysis, 3D metrology and vector search
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Leading the data pipeline strategy for a 500,000 image proprietary dataset - anonymisation, auto-labelling, structuring and training readiness
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Defining and managing fallback model strategies for offline and low-connectivity environments
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Ensuring EU data residency and compliance requirements are met across all model and infrastructure choices
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Liaising with an academic research partner to translate R&D output into production-ready components
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Mentoring and guiding the Computer Vision Engineer, ML Engineer, Senior Mobile Developer, Backend and Data Engineer, and Salesforce Integration Specialist
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Maintaining architectural coherence as requirements evolve and as the AI landscape shifts during the build period
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Building and sustaining a team culture of constructive challenge, accountability and mutual respect
What Makes This Role Exceptional
The technical complexity of this project is not manufactured to sound impressive on a job description. You will be architecting a real production system, on a real timeline, with a real proprietary dataset, for a real enterprise client. Every architectural decision you make will have measurable consequences.
You will have genuine autonomy, a capable team, an academic partner for the research-heavy components, and the freedom to challenge every technology choice on the table. If you are the kind of person who finds complexity energising rather than exhausting, this role was built for you.
How We Hire
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Requirements
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10 to 15 years of hands-on AI and machine learning experience, with demonstrable production deployments at scale
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PhD in Artificial Intelligence, Computer Science or Machine Learning strongly preferred; publications in computer vision, multimodal AI or related fields are a significant advantage
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Broad and current knowledge of the AI model landscape - you know what exists, what is emerging, and how to evaluate competing tools objectively
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Experience designing hybrid edge and cloud inference architectures with offline-first constraints
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Proven ability to lead senior technical teams through complex, fast-moving projects where the ground shifts beneath you
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Comfortable operating at the intersection of academic research partnerships and commercial delivery
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A natural ability to facilitate difficult technical conversations and bring a team to constructive conclusions without ego or politics
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Fluency in English required; Italian is a strong advantage
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