About StarCompliance
StarCompliance is a market-leading provider of employee compliance technology, trusted by 350+ global financial institutions and highly regulated organisations to manage regulatory obligations, monitor employee activity, and mitigate risk. Backed by private equity, we are investing in the next generation of our cloud-native, AI-enabled SaaS platform — and this role will shape the AI and data future of that platform.
Role:
We need a hands-on technical leader to own our data and AI strategy and execute it — building a high-performing Data & AI function that ships production-grade AI capabilities at scale in a heavily regulated environment.
You will partner closely with Product, Engineering, Architecture, Security, and the executive team. You will work together with the Product Director, AI & Data Products as a joint technology-and-product leadership pairing, co-owning the AI roadmap, prioritisation, and delivery outcomes.
Responsibilities:
Own the end-to-end technical strategy and execution roadmap for AI-enabled product capabilities across the StarCompliance platform.
Drive adoption of generative AI, LLM-based architectures, predictive analytics, graph intelligence, recommendation systems, and semantic search where these deliver measurable customer value.
Own the data foundation strategy, ensuring clean, trusted, well-governed data underpins every AI initiative.
Build robust MLOps capabilities, including model training pipelines, versioning, monitoring, A/B experimentation, and drift detection.
Champion pragmatic AI adoption within engineering and product development, accelerating how we build, not just what we build.
Build, mentor, and scale a high-performing Data & AI organisation across data engineering, data science, ML engineering and analytics.
Work closely with the CTO and executive team to align AI and data initiatives with company strategy and commercial priorities.
Partner with the Product Director, AI & Data Products, co-owning the AI roadmap, prioritisation, and delivery outcomes.
AI Product Delivery & Strategy
Data Platform & Engineering
Internal AI Enablement
Leadership & Team Building
Cross-Functional & Executive Collaboration
Skills and Experience:
Proven delivery of production-grade AI and ML systems at scale, not just experimentation.
Deep experience with generative AI and LLM-based application architectures (fine-tuning, prompt engineering, RAG, agentic frameworks).
Strong knowledge of vector databases and semantic search (e.g. Pinecone, Weaviate, pgvector, Azure AI Search).
Deep background in modern data engineering, ELT/ETL patterns, and large-scale data pipeline architectures.
Hands-on experience with Snowflake (or equivalent cloud data warehouse) and associated data modelling patterns.
Strong Azure ecosystem experience: Azure Data Factory, Azure Synapse, Azure OpenAI Service, and Azure Machine Learning.
Strong software engineering fundamentals and the credibility to engage at technical depth with senior engineers.
Experience with cloud-native, microservices, and event-driven architectures on Azure (or equivalent hyperscaler).
Ability to make sound build vs buy vs integrate decisions across the AI and data tooling landscape.
Proven experience building and leading high-performing Data / AI engineering teams.
Experience within financial services, regtech, compliance, surveillance, or similarly regulated domains.
Strong commercial instincts — the ability to connect technical investment to customer value and business outcomes.
AI & Machine Learning
Data Engineering & Platforms
Software Engineering & Architecture
Leadership & Business
Integrity and Ethics
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