Hybrid Senior AI Engineer

at Aurora Energy Research

• Job title: Senior AI Engineer
• Job type: Full Time
• Experience level: Senior
• Salary: Not specified
• Degree requirement: Postgraduate Degree
• Tech skills: AWS, Cloud, Docker, EC2, Node.js, Python, PyTorch, Scikit-Learn, Tensorflow, Terraform, TypeScript
• Location requirements: Hybrid, Oxford, United Kingdom

About the role

• Senior AI Engineer developing AI-driven services and solutions using state-of-the-art AI technologies. Collaborating with product managers to integrate AI into software platforms at Aurora.

Responsibilities

• Architect and develop AI-driven services using large language models, Retrieval Augmented Generation (RAG) pipelines, and multi-agent orchestration (using frameworks like LangGraph) to power key products and internal tools
• Design robust AI systems from concept to deployment, ensuring they are scalable, reliable, and deliver value for end-users
• Work closely with product managers and stakeholders to integrate AI capabilities into software platforms
• Deploy solutions on cloud infrastructure (including AWS Lambdas for serverless compute) and using modern MLOps practices to monitor and improve them in production
• Provide technical leadership, driving architectural decisions, mentoring junior engineers, and championing best practices in AI development
• Act as a key evangelist for AI-assisted engineering to ensure that Aurora leverages AI tooling effectively to achieve engineering excellence

Requirements

• Extensive experience in AI/ML development, 5+ years building complex software solutions with a focus on machine learning and AI
• Strong expertise in Python programming. Experience with ML frameworks such as scikit-learn, PyTorch, or TensorFlow is expected. Familiarity with Node/TypeScript is a plus
• Hands-on experience with modern AI/LLM tooling. We are looking for comfort with frameworks and libraries like LangGraph for building LLM applications
• Proven experience deploying and operating AI solutions on cloud platforms (AWS preferred). You have used cloud services like AWS Lambda (or EC2/ECS) to host models or run AI workloads, and are familiar with data storage options (S3, databases). Experience with CI/CD pipelines for rapid deployment, containerisation (Docker), and automating infrastructure (Terraform/CloudFormation or similar) is required to manage our AI services lifecycle
• Exceptional analytical and problem-solving skills. You can break down ambiguous problems (like improving an AI model’s relevance or figuring out why a pipeline is slow) and iterate to develop effective solutions
• Demonstrated ability to design and interpret complex quantitative analyses, using prototypes to translate insights into actionable strategies for business and product teams. Experience mentoring junior engineers or data scientists (providing guidance, code reviews, and fostering best practices) is required, as this role will help shape the growth of our AI team
• Excellent communication and collaboration abilities. You can effectively communicate complex AI concepts to different audiences, whether it’s explaining model results and limitations to product stakeholders or discussing technical details with fellow engineers
• A Master’s or PhD in a relevant field (Computer Science, AI, Machine Learning, etc.) is a plus
• Background in the energy sector or similar domains is not required, but familiarity with handling time-series data, simulation models, or financial/market data could be beneficial since our company operates in the energy market space
• While your focus is AI, any experience building front-ends or full-stack applications can be helpful, as it indicates you understand how AI features need to plug into a product

Benefits

• Private Medical Insurance
• Dental Insurance
• Parental Support
• Salary-Exchange Pension
• Employee Assistance Programme (EAP)
• Local Oxford Discounts
• Cycle-to-work Scheme
• Flu Jabs