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Senior Solutions Architect (Data and AI)

Aventum Group Management Services Ltd

London, GBR

Full-time

Senior · 3+ years experience

Hybrid

Discovered 6 days ago

ProfiseeLarge Language Models (LLMs)Retrieval-Augmented Generation (RAG)Azure

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ProfiseeLarge Language Models (LLMs)Retrieval-Augmented Generation (RAG)

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Group data architecture. Own the target data architecture across Aventum's product estate: domain models, canonical entities, and the integration patterns by which data moves between products designed once, documented as production artefacts, and kept current.
Master data management. Own MDM on Profisee: golden-record strategy, match/merge rules, survivorship, stewardship workflows, and the reference data and lists shared across products so every product builds on the same settled facts.
Data contracts. Define and enforce data contracts between products and with third parties: schemas, versioning, ownership, and failure behaviour agreed before build, so downstream AI and analytics workloads have reliable, well-defined inputs.
AI product architecture. Design and build the AI products that run on this data: LLM-based capabilities, agentic workflows, retrieval over mastered data, and integration of AI components into our product platforms.
Evaluation and guardrails. Own how we make probabilistic systems safe and measurable: evaluation harnesses, test packs for AI behaviour, monitoring, and the guardrails appropriate to a regulated insurance business.
Specification. Work inside the spec-driven model: contribute to Design Alignment Workshops, review BRDs for data and AI feasibility before sign-off, and produce designs precise enough that engineers and AI agents can build against them without interpretation.
Data quality and governance. Set and enforce data quality standards in partnership with underwriting, operations, and compliance lineage, controls, and the evidence that regulators and auditors expect.
Build vs buy. Advise on model, platform and tooling selection with clear-eyed judgment about cost, risk, and regulatory exposure and the discipline to choose boring technology where boring is right.
Working with the teams. Act as the data and AI design counterpart to Tech Leads and Principal Engineers across the product teams; resolve architectural questions before they surface as blockers in a build.
Proven experience as a Data Architect, Solutions Architect (Data/AI), or similar, with a minimum of 3 years owning enterprise or group-level data architecture.
Demonstrated experience delivering AI, Generative AI, or LLM-based products into production environments, with accountability for the underlying data architecture.
Extensive experience in master data management (MDM), including platforms such as Profisee or equivalent.
Strong background in data modelling, integration architecture, API design, event-driven architectures, and enterprise data flows.
Experience designing and implementing cloud-based data platforms, with Azure experience preferred.
Previous experience working within regulated industries, ideally insurance or financial services.
Strong understanding of insurance data domains, including policy, claims, customer/party, and reference data.
Proven ability to engage and influence stakeholders across underwriting, operations, compliance, and technology functions.
Deep expertise in modern AI and Data Architecture, including: Large Language Models (LLMs). Retrieval-Augmented Generation (RAG). Agentic AI architectures. AI integration and orchestration patterns.
Evaluation and monitoring of probabilistic AI systems.
Hands-on capability to work with AI-powered development tools and coding agents, delivering solutions at pace.
Strong technical understanding of data governance, data quality, metadata management, and enterprise data standards.
Exceptional written and verbal communication skills with the ability to produce clear, precise, testable, and unambiguous architectural documentation.
Ability to translate complex business requirements into scalable and sustainable technical solutions.
Excellent stakeholder management and influencing skills, with proven ability to build consensus across competing business priorities.
Strong analytical, problem-solving, and strategic thinking capabilities.
Ability to balance innovation with governance, compliance, and operational requirements in a regulated environment.
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