AI Software Engineer

We are Global Logic, a Hitachi Group Company and a leader in digital engineering. We help brands across the globe design and build innovative products, platforms, and digital experiences for the modern world. By integrating experience design, complex engineering, and data expertise, we help our clients imagine what’s possible and accelerate their transition into tomorrow’s digital businesses.

This is a 12‑month assignment (inside IR35) to start in 2–4 weeks. The role is a hands‑on, high‑impact position at the intersection of AI governance, distributed systems, observability, and platform engineering. You will lead technical delivery for an AI centralised platform – Control Tower – as part of a cross‑functional team building pipelines, services, and monitoring capabilities. You will develop core components of an AI platform, contribute to its evolution, and ensure our AI systems are measurable, transparent, and well‑controlled from model training through to production.

• Build and enhance platform capabilities by developing 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.
• Engineer a robust, resilient, and secure AI environment with high‑throughput pipelines capturing model performance, drift, operational health, and security posture.
• Implement observability tooling using logging, metrics, tracing, and event‑driven patterns.
• Apply secure‑by‑design principles, strong IAM practices, and cloud security controls.
• Work closely with data engineering, platform engineering, security, MLOps, and monitoring teams to integrate with AWS Sage Maker, model pipelines, and enterprise data platforms.
• Support governance and reporting workflows with automated checks, standardised metrics, and platform tooling.
• Contribute to reusable components, shared libraries, and engineering patterns, and participate in adopting new technologies around Responsible AI, observability, and runtime monitoring.
• Support continuous improvement of CI/CD, infrastructure‑as‑code, and testing practices.

• Hands‑on engineer who enjoys solving complex data and observability problems and is passionate about building safe, transparent, and reliable AI systems.
• 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 Sage Maker (required).
• Understanding of monitoring frameworks, observability pipelines, and dashboards.
• Familiarity with event‑driven architectures and messaging systems.
• Knowledge of security engineering, IAM principles, encryption, and cloud security controls.
• Awareness of model risk and regulatory frameworks, and understanding of operational resilience concepts and SRE practices (SLIs/SLOs).
• Experience with data lineage or governance tooling (Data Hub, Glue, Collibra).
• Interest in Responsible AI, explainability, fairness/bias, and governance automation.
• Experience with CI/CD, infrastructure‑as‑code, and automated testing for data/ML systems.

Location:

UK&I region. The role supports a hybrid model with flexible working options.

We are an equal opportunities employer. It is our policy to promote an environment free from discrimination, harassment and victimisation.