At a Glance
- Tasks: Build AI pipelines and services, ensuring observability and governance across the bank's systems.
- Company: Join a leading banking client in a dynamic hybrid work environment.
- Benefits: Enjoy competitive pay, flexible working, and opportunities for professional growth.
- Other info: Collaborate with diverse teams in a fast-paced, innovative setting.
- Why this job: Make a real impact in AI governance while working with cutting-edge technologies.
- Qualifications: Strong Python, SQL skills, and experience with cloud-based AI/ML ecosystems required.
The predicted salary is between 60000 - 80000 £ per year.
Hybrid Working - London - 2 days a week on site. Lorien's leading banking client is looking for an exceptional AI Engineer with strong experience in Python, SQL, and working with Cloud Based AI/ML Ecosystems, and AWS SageMaker. This role will be building the pipelines, services, and monitoring capabilities that underpin AI observability and governance across the bank. This is a hands-on, high-impact role at the intersection of AI governance, distributed systems, observability, and platform engineering. You will develop core components of the platform, contribute to its evolution, and ensure our AI systems are measurable, transparent, and well-controlled from model training through to production.
The Ideal Candidate will have:
- Strong engineering foundations, with experience building scalable distributed systems or data platforms.
- Proficiency in Python, SQL, Java, and modern data processing frameworks.
- Experience working with cloud-based AI/ML ecosystems, particularly AWS SageMaker (required).
This role is based in London. This role will be Via Umbrella. Working in a Hybrid Model of 2 days a week on site.
What You'll Do
- Contribute to the development of data pipelines, APIs, and services that power the AI Control Tower.
- Implement components supporting AI observability, guardrails, performance monitoring, and lifecycle controls.
- Develop integrations with model registries, feature stores, lineage tools, and governance systems.
- Write clean, well-tested, scalable code in Python, Java, SQL, and modern data/stream processing frameworks.
- Build high-throughput pipelines to capture metrics such as:
- Model performance, drift, and degradation
- Operational and service health
- Security posture and policy adherence
- Guardrail compliance for ML and GenAI systems
- Governance and risk indicators
- Implement observability tooling using logging, metrics, tracing, and event-driven patterns.
- Support monitoring and measurement of AI systems across development, deployment, and runtime environments.
- Work closely with data engineering, platform engineering, security, MLOps, and Independent Model Monitoring (IMM) teams.
- Contribute to integration efforts with AWS SageMaker, model pipelines, and enterprise data platforms.
- Use technologies such as AWS, SageMaker, Python, Java, Kafka, OpenTelemetry, and cloud-native monitoring stacks.
- Support governance and reporting workflows with automated checks, standardised metrics, and platform tooling.
- Understanding of monitoring frameworks, observability pipelines, and dashboards.
- Familiarity of event-driven architectures and messaging systems (Kafka, Vert.x, or similar).
- Knowledge of security engineering, IAM principles, encryption, and cloud security controls.
- Experience with CI/CD, infrastructure-as-code, and automated testing for data/ML systems.
Helpful Experience
- Exposure to MLOps, LLMOps, or model lifecycle management.
- Awareness of model risk and regulatory frameworks (e.g., SS1/23, NIST AI Risk Management Framework).
- Understanding of operational resilience concepts and SRE practices (SLIs/SLOs).
- Experience with data lineage or governance tooling (DataHub, Glue, Collibra).
- Interest in Responsible AI, explainability, fairness/bias, and governance automation.
AI Engineer in London employer: Lorien
Join a leading banking client in London as an AI Engineer, where you'll thrive in a hybrid working environment that promotes flexibility and work-life balance. With a strong focus on innovation and employee development, the company offers exceptional growth opportunities, a collaborative culture, and the chance to work on high-impact projects at the forefront of AI governance and observability. Enjoy the benefits of working in a dynamic team while contributing to cutting-edge technology that shapes the future of banking.
StudySmarter Expert Advice🤫
We think this is how you could land AI Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, SQL, and AWS SageMaker. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice common interview questions related to AI governance and distributed systems, and be ready to discuss your past experiences in detail.
✨Tip Number 4
Don't forget to apply through our website! We make it easy for you to find roles that match your skills and interests. Plus, applying directly can sometimes give you an edge over other candidates.
We think you need these skills to ace AI Engineer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with Python, SQL, and AWS SageMaker. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about AI governance and how your background makes you a perfect fit for our team. Keep it engaging and personal – we love to see your personality!
Showcase Your Projects:If you've worked on any cool AI/ML projects, make sure to mention them! Whether it's building data pipelines or implementing observability tooling, we want to know what you've done and how it relates to the role.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity. Plus, it’s super easy!
How to prepare for a job interview at Lorien
✨Know Your Tech Stack
Make sure you brush up on your Python, SQL, and AWS SageMaker skills. Be ready to discuss specific projects where you've used these technologies, as well as any challenges you faced and how you overcame them.
✨Understand AI Governance
Since this role involves AI observability and governance, it’s crucial to familiarise yourself with relevant frameworks and best practices. Prepare to talk about how you’ve implemented governance in past projects and the importance of transparency in AI systems.
✨Showcase Your Problem-Solving Skills
Be prepared to tackle hypothetical scenarios or technical problems during the interview. Think through your approach to building scalable distributed systems and how you would ensure performance monitoring and lifecycle controls are in place.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the team’s current projects, the company’s approach to AI governance, and how they measure success in their AI initiatives. This shows your genuine interest and helps you gauge if it’s the right fit for you.
