AI Software Engineer

Lorien; City Of London; Hybrid; GBP 60,000 - 80,000; Full time

Job summary

A leading banking client is seeking an AI Software Engineer to join a cross-functional team in London. The role involves building AI observability and governance, developing data pipelines, and implementing observability tools using technologies like Python, AWS SageMaker, and Kafka. Candidates should have strong skills in distributed systems and cloud-based AI ecosystems. This is a hybrid position requiring on-site work twice a week.

Qualifications

• Strong engineering foundations in scalable distributed systems.
• Experience with cloud-based AI/ML ecosystems.
• Proficiency in Python, SQL, and Java.

Responsibilities

• Develop data pipelines, APIs, and services for AI Control Tower.
• Implement AI observability components and lifecycle controls.
• Collaborate with engineering teams on AI system integration.

Skills

Python

SQL

Java

AWS SageMaker

Kafka

Tools

AWS

Open Telemetry

CI/CD

Job description

Hybrid Working - Edinburgh OR London - 2 days a week on site.

Lorien's leading banking client is looking for a AI Software Engineer who will work as part of a cross‑functional engineering team to build 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.

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, Open Telemetry, and cloud‑native monitoring stacks.
• Support governance and reporting workflows with automated checks, standardised metrics, and platform tooling.
• Contribute to reusable components, shared libraries, and engineering patterns.
• Participate in adopting new technologies around Responsible AI, observability, and runtime monitoring.
• Support continuous improvement of CI/CD, infrastructure‑as‑code, and testing practices.

Key Skills and Experience

• 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).
• 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

Guidant, Carbon60, Lorien & SRG - The Impellam Group Portfolio are acting as an Employment Business in relation to this vacancy.