AI / ML Services Engineer

• Design, develop and maintain production-grade agentic AI systems, including tool integration, memory, orchestration and failure handling.
• Evaluate AI agents and model performance using repeatable datasets, quality metrics, regression testing and human feedback.
• Implement model adaptation and optimisation techniques, including supervised fine-tuning, preference-based or reinforcement learning approaches, and LoRA/QLoRA.
• Develop enterprise search, document processing and retrieval solutions using vector search, relational databases or graph-based technologies.
• Deploy, monitor and troubleshoot AI services and applications running on Kubernetes.
• Diagnose issues across distributed, asynchronous and GPU-backed workloads.
• Build and maintain containerised applications using Docker and Kubernetes, supporting scalable and reliable deployments.
• Contribute to cloud-native development across GCP, AWS or Azure, working with CI/CD pipelines and version control.
• Design secure, maintainable software and proactively identify potential security risks.

• Hands-on experience building and deploying production agentic AI systems using frameworks such as LangGraph, AutoGen, Google ADK, AWS Strands or equivalent.
• Experience evaluating AI agent and model behaviour through automated testing, quality metrics and regression frameworks.
• Production experience in model adaptation or fine-tuning, including SFT and at least one additional technique such as reinforcement or preference-based tuning, LoRA/QLoRA, distillation or teacher/student approaches.
• Experience with enterprise search, document AI or graph-based retrieval, alongside technologies such as Elasticsearch, SQL/PostgreSQL, vector databases or graph databases.
• Practical experience deploying and debugging Kubernetes applications, including workloads, configuration, autoscaling, resource utilisation, logs, metrics and traces.
• Experience with distributed systems, asynchronous processing or GPU-backed workloads.
• Production experience with at least one major cloud platform: GCP, AWS or Azure.
• Experience with Docker, CI/CD pipelines and version control tools such as Git, GitLab or Bitbucket.

• Experience with multiple cloud platforms.
• Go programming experience.
• Experience developing administrative command consoles or data-heavy dashboards.
• Familiarity with Enterprise Content Management (ECM), Business Process Management (BPM) or Intelligent Document Processing (IDP) systems.
• Experience working with global engineering teams across product, infrastructure and operations.

If you are interested in this opportunity, please apply now with your updated CV in Microsoft Word/PDF format.

Disclaimer
Notwithstanding any guidelines given to level of experience sought, we will consider candidates from outside this range if they can demonstrate the necessary competencies.
Square One is acting as both an employment agency and an employment business, and is an equal opportunities recruitment business. Square One embraces diversity and will treat everyone equally. Please see our website for our full diversity statement.