Head of Data & AI - UK Based

Responsibilities

AI Product Delivery & Strategy

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Own the end-to-end technical strategy and execution roadmap for AI-enabled product capabilities across the StarCompliance platform.

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Drive adoption of generative AI, LLM-based architectures, predictive analytics, graph intelligence, recommendation systems, and semantic search where these deliver measurable customer value.

Data Platform & Engineering

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• Own the data foundation strategy, ensuring clean, trusted, well-governed data underpins every AI initiative.
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• Build robust MLOps capabilities, including model training pipelines, versioning, monitoring, A/B experimentation, and drift detection.

Internal AI Enablement

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• Champion pragmatic AI adoption within engineering and product development, accelerating how we build, not just what we build.

Leadership & Team Building

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• Build, mentor, and scale a high-performing Data & AI organisation across data engineering, data science, ML engineering and analytics.

Cross-Functional & Executive Collaboration

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• Work closely with the CTO and executive team to align AI and data initiatives with company strategy and commercial priorities.
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• Partner with the Product Director, AI & Data Products, co-owning the AI roadmap, prioritisation, and delivery outcomes.

Skills and Experience

AI & Machine Learning

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• Proven delivery of production-grade AI and ML systems at scale, not just experimentation.
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• Deep experience with generative AI and LLM-based application architectures (fine-tuning, prompt engineering, RAG, agentic frameworks).
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• Strong knowledge of vector databases and semantic search (e.g. Pinecone, Weaviate, pgvector, Azure AI Search).

Data Engineering & Platforms

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• Deep background in modern data engineering, ELT/ETL patterns, and large-scale data pipeline architectures.
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• Hands-on experience with Snowflake (or equivalent cloud data warehouse) and associated data modelling patterns.
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• Strong Azure ecosystem experience: Azure Data Factory, Azure Synapse, Azure OpenAI Service, and Azure Machine Learning.

Software Engineering & Architecture

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• Strong software engineering fundamentals and the credibility to engage at technical depth with senior engineers.
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• Experience with cloud-native, microservices, and event-driven architectures on Azure (or equivalent hyperscaler).
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• Ability to make sound build vs buy vs integrate decisions across the AI and data tooling landscape.

Leadership & Business

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• Proven experience building and leading high-performing Data / AI engineering teams.
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• Experience within financial services, regtech, compliance, surveillance, or similarly regulated domains.
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• Strong commercial instincts — the ability to connect technical investment to customer value and business outcomes.

Integrity and Ethics

All StarCompliance employees are expected to commit to a high standard of personal integrity and carry out their responsibilities in an ethical manner.