AI Engineer

We are seeking a hands-on AI/ML Engineer to build, deploy, and optimize machine learning and generative AI solutions. The role focuses on developing production-grade AI applications, integrating AI models into business systems, and supporting the full AI development lifecycle. The ideal candidate is passionate about modern AI technologies, software engineering best practices, and delivering reliable AI solutions at scale.

Responsibilities

• Machine Learning Engineering
• Train, fine-tune, evaluate, and deploy ML models.
• Develop feature engineering and model evaluation pipelines.
• Implement model monitoring and performance tracking.
• Optimize model inference performance and cost efficiency.
• Generative AI Engineering
• Develop LLM-based applications and workflows.
• Build prompt templates, agent frameworks, and orchestration pipelines.
• Implement vector search and knowledge retrieval systems.
• Design evaluation frameworks for AI quality, safety, and reliability.
• Improve hallucination mitigation and response accuracy.
• MLOps & Deployment
• Design and automate ML model training, validation, and retraining pipelines.
• Version and manage datasets, features, and model artefacts using tools such as MLflow.
• Deploy and serve ML models via REST APIs or batch inference at scale on Databricks, Snowflake or similar.
• Monitor model performance in production, detecting drift and degradation.
• Manage feature stores and ensure data pipeline reliability for ML workloads.
• Implement experiment tracking and reproducibility across the model lifecycle.
• Collaboration
• Work closely with Solution Architects, Product Managers, and Engineering Teams.
• Participate in code reviews and technical design discussions.
• Support testing, deployment, and ongoing optimisation activities.
• Programming & Engineering Skills
• Strong proficiency in: Python, SQL
• Experience with: Scikit-learn, RAG systems, AI agents, LLM-powered applications, vector search solutions
• Familiarity with: LangChain, LlamaIndex, Semantic Kernel, LangGraph
• Cloud & Infrastructure: AWS, Azure, or GCP
• Docker and containerization
• Kubernetes (preferred)
• CI/CD pipelines and DevOps practices
• Qualifications
• 3+ years in ML engineering or data science, with demonstrable experience deploying models to production and building Gen AI applications including RAG systems, LLM integration, or agentic workflows.
• Demonstrated experience delivering AI solutions into production environments.
• Benefits
• Share in our success with a Quarterly Performance-Related Profit Share Scheme.
• Strong career progression & mentorship coaching through dedicated career development programmes.
• Flexible/remote working arrangements.
• Financial wellbeing initiatives: pension, private healthcare cover, life assurance, financial advice, employee discount scheme.
• Employee wellbeing schemes including gym discounts, bike-to-work, fitness classes, mindfulness workshops, and an employee assistance programme.
• Generous holiday allowance, enhanced maternity/paternity leave, marriage/civil partnership leave, and special leave policies.
• Educational assistance and incentives for certifications and accreditations (AWS, Microsoft, Oracle, Red Hat).
• Reward schemes including annual excellence awards and a ‘Call-Out’ platform.
• Environment, Social and Community First initiatives, fostering diversity, inclusion and belonging.