обновлено 3 дня назад
Staff Engineer (Data & AI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Staff Engineer (Data & AI): Leading the architecture of Arbor’s data platform across OLTP, OLAP, and AI foundations with an accent on data governance, cloud-native distributed systems, and AI-first engineering. Focus on designing LLM orchestration, RAG, and real-time inference infrastructure, aligning technical direction with product goals, and coaching engineering leaders across multiple teams.
Location: Remote, United Kingdom
Company
develops MIS and school management tools used by more than 12,000 schools and trusts, helping education staff work with clearer data and more effective processes.
What you will do
- Define and communicate target architectures spanning transactional, analytical, and AI systems.
- Own the end-to-end data lifecycle, including OLTP schema design, migrations, OLAP governance, platform engineering, and analytics.
- Guide Technical Leads on feature delivery, technical debt reduction, architecture improvements, and engineering quality.
- Partner with Product Directors and Engineering Management to translate product strategy into technical outcomes and remove systemic bottlenecks.
- Lead the shift toward AI-first engineering and architect foundations for LLM orchestration, Retrieval-Augmented Generation, and real-time model inference at scale.
- Mentor Technical Leads and Senior Engineers, lead architectural reviews, and shape broader technology strategy with Staff and Principal Engineers.
Requirements
- Extensive experience overseeing data architecture and delivering iterative outcomes across OLAP domains.
- Strong knowledge of data modelling, distributed data systems, and cloud-native platforms such as Snowflake.
- Experience working across multiple data disciplines, including platform, analytics, data science, or AI.
- Ability to influence technical and non-technical stakeholders and support engineers across distributed, cross-functional teams.
- Practical knowledge of DataOps, CI/CD for data, complex pipeline orchestration, AWS, Debezium, Git, and infrastructure as code.
- Knowledge of data security, encryption, compliance, platform cost optimisation, and forecasting models.
Nice to have
- AI/ML engineering and MLOps experience, including model deployment, serving, and monitoring.
- Experience with federated learning or privacy-enhancing technologies.
- LLM Ops experience, including prompt engineering at scale and token cost optimisation.
Culture & Benefits
- Flexible remote working and a dedicated wellbeing programme.
- 32 days of holiday plus Bank Holidays.
- Life assurance at three times annual salary, private dental insurance, pension, and enhanced parental leave.
- 24/7 virtual GP access, mental health support, counselling, and financial wellbeing services.
- Professional development budget, social committees, and one paid volunteering day each year.
- Visa sponsorship is not available.
Hiring process
- Phone screen.
- First-stage interview.
- Second-stage interview.
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