AI Engineer
Role details
Job location
Tech stack
Job description
- Maintain and enforce best practices for AI engineering and governance within the Lakehouse architecture,
- ensuring compliance and security standards.
- Integrate generative AI capabilities (e.g., Databricks Genie) into business workflows to automate
- processes and deliver advanced analytics solution.
- Operationalise AI and machine learning models within the Databricks Lakehouse environment, including
- deployment, monitoring, and optimisation of data pipelines.
- Collaborate with cross-functional teams to embed AI-driven insights into core business processes, ensuring alignment with Lloyd's Data & AI strategy.
- Contribute to the development of Lloyd's Data & AI Marketplace, supporting innovation and enabling self-service analytics capabilities for stakeholders.
- Drive continuous improvement and innovation by researching emerging trends in AI, ML, and visualisation technologies, recommending enhancements to tools and processes.
- Provide technical leadership and knowledge sharing within the AI & Analytics team, mentoring colleagues on visualisation techniques and AI engineering practices.
- Monitor and report on performance and adoption of AI solutions, ensuring measurable business impact and alignment with strategic objectives.
Skills Knowledge and Experience
Lakehouse & Data Engineering
- Databricks SQL, Delta Lake, pipeline orchestration, Unity Catalog
- Azure data governance and performance optimisation
- Built secure, scalable Lakehouse pipelines and data products
ML Engineering & MLOps
- Python/SQL for ML, CI/CD, automated testing, monitoring
- Experience deploying and maintaining ML models with drift/quality controls
GenAI & Agentic Systems
- LLM orchestration, secure prompting, RAG, vector search
- Delivered GenAI PoCs and workflow-embedded solutions
Solution Design & SDLC
- Designing reference architectures, defining NFRs, Agile delivery
- Created solution designs through to production with strong governance alignment
Observability & Performance
- Telemetry, metrics, SLOs, cost optimisation
- Improved pipeline reliability and reduced run-costs
Collaboration & Leadership
- Cross-functional partnering, code reviews, mentoring
- Enabled teams to adopt standards and influenced platform evolution
Continuous Innovation
- Rapid prototyping, vendor evaluation, cost-value assessment
- Converted PoCs into production solutions, We understand that our work/life balance is important to us all and that a hybrid of working from the office and home can offer a great level of flexibility. Flexible working forms part of a total reward approach which offers a host of other benefits over and above the standard offering (generous pension, healthcare, wellbeing etc). These include financial support for training, education & development, a benefit allowance (to spend on our flexible benefits such as gym membership, dental insurance, extra holiday or to partake in our cycle to work scheme), employee recognition scheme and various employee discount schemes.
Requirements
- Postgraduate degree in a relevant field
- Professional experience or certifications in data architecture, business intelligence, data engineering, or analytics
Diversity and inclusion are a focus for us - Lloyd's aim is to build a diverse, inclusive environment that reflects the global markets we work in. One where everyone is treated with dignity and respect to achieve their full potential. In practice, this means we are positive and inclusive about making workplace adjustments,we offer regular health and wellbeing programmes, diversity and inclusion training, employee networks, mentoring and volunteering opportunities as well as investment into your professional development. You can read more about diversity and inclusion on our website .