Senior Software Engineer (Contract) in London

Senior Software Engineer (Contract) in London

London Full-Time 70000 - 90000 £ / year (est.) No working from home possible
GlobalLogic

At a Glance

  • Tasks: Join us to build innovative AI platforms and enhance data pipelines.
  • Company: GlobalLogic, a leader in digital engineering and innovation.
  • Benefits: Hybrid work model, inclusive culture, and generous training budget.
  • Other info: Dynamic team environment with opportunities for career growth.
  • Why this job: Make a real impact in AI governance and platform engineering.
  • Qualifications: Experience in Python, SQL, Java, and cloud-based AI ecosystems required.

The predicted salary is between 70000 - 90000 £ per year.

We are GlobalLogic, 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.

We are seeking to hire an experienced Contract Software Engineer / AI Platform Software Engineer into our project team. This is a 12 month assignment (inside IR35), to start in 2-4 weeks. This is a hands-on, high impact role at the intersection of AI governance, distributed systems, observability, and platform engineering to lead technical delivery for an AI centralised platform - Control Tower.

We’re looking for a Software Engineer who will work as part of a cross-functional engineering team to build the 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.

What We’re Looking For:

  • 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 SageMaker (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.
  • 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.
  • Experience with CI/CD, infrastructure-as-code, and automated testing for data/ML systems.

What You’ll Do:

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

We hire based on expertise, potential, and enthusiasm to make a difference, then we give you the tools and skills you need to create impact. This role is based in our UK&I region - hybrid either London or Edinburgh.

Why work at GlobalLogic:

Our goal is to build an inclusive, positive culture where everyone can feel comfortable being themselves, empowering our people to create their own high standards and therefore more value. We work together to promote fairness while recognising, valuing, and embracing differences – providing a transparent support structure and generous training budget to help our people develop skills to progress their career. Our region also supports a hybrid model which can flex across a wide spectrum of working options determined by our business, customer, and individual needs.

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

Senior Software Engineer (Contract) in London employer: GlobalLogic

At GlobalLogic, we pride ourselves on fostering an inclusive and positive work culture that empowers our employees to thrive. With a strong commitment to professional development, we offer generous training budgets and a flexible hybrid working model in vibrant locations like London and Edinburgh, ensuring that our team members can balance their personal and professional lives while contributing to innovative projects in digital engineering.

GlobalLogic

Contact Details:

GlobalLogic Recruitment Team

We think you need these skills to ace Senior Software Engineer (Contract) in London

Python
SQL
Java
AWS SageMaker
Data Processing Frameworks
Distributed Systems
Observability