AI Engineer
Hybrid Working - London - 2 days a week on site.
Financial Services
Lorien's leading banking client is looking for an exceptionalAI Engineer with strong experience inPython, 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 ofAI 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 inPython, SQL, Java, and modern data processing frameworks.
- Experience working withcloud-based AI/ML ecosystems, particularlyAWS 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.
Essential Skills & Experience
- 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.
- Apply secure-by-design principles, strong IAM practices, and cloud security controls.
- 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.
Essential Skills
- Strong engineering foundations, with experience building scalable distributed systems or data platforms.
- Proficiency inPython, SQL, Java, and modern data processing frameworks.
- Experience working withcloud-based AI/ML ecosystems, particularlyAWS SageMaker (required).
- Understanding ofmonitoring frameworks, observability pipelines, and dashboards.
- Familiarity ofevent-driven architectures and messaging systems (Kafka, Vert.x, or similar).
- Knowledge ofsecurity engineering, IAM principles, encryption, and cloud security controls.
- Experience withCI/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
IND_PC3
Guidant, Carbon60, Lorien & SRG - The Impellam Group Portfolio are acting as an Employment Business in relation to this vacancy.
:quality(80))
:quality(80))
:quality(80))