Based in Oxford, you will work as part of a growing AI software team that is building innovative intelligent solutions. As a Senior AI Engineer, you will 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 at Aurora.
You will turn product ideas into reality by designing robust AI systems from concept to deployment, ensuring they are scalable, reliable, and deliver value for end-users. This role involves working closely with our product managers and stakeholders to integrate AI capabilities into our software platforms. You will be deploying these solutions on cloud infrastructure (including AWS Lambdas for serverless compute) and using modern MLOps practices to monitor and improve them in production.
As a senior member of the team, you will also provide technical leadership, driving architectural decisions, mentoring junior engineers, and championing best practices in AI development. You will also act as a key evangelist for AI-assisted engineering to ensure that Aurora leverages AI tooling effectively to achieve engineering excellence.
Key Responsibilities
- Design and develop AI solutions, taking end-to-end ownership of AI features
- Build and maintain RAG pipelines, agentic orchestration, developing agent-based systems for complex multi-step tasks. Establish robust evaluation methods to measure the quality of our solutions, and its component parts
- Identify and evaluate new data sources, design robust, scalable data pipelines
- Deploy and scale AI solutions on AWS cloud infrastructure
- Work closely with the broader software engineering team and stakeholders (internal and external) to innovate highly effective solutions
- Mentor and coach junior and mid-level engineers, fostering their growth
- Monitor the performance and accuracy of deployed AI solutions and iterate to improve them
- Champion a culture of innovation, continuous learning, and operational excellence
Skills, Knowledge and Expertise
Required attributes
- 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 translating 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
What we offer
Some of the benefits we include are:
- Private Medical Insurance
- Parental Support
- Employee Assistance Programme (EAP)
- Local Oxford Discounts
- Cycle-to-work Scheme
- Flu Jabs
At AER, we are committed to offering flexibility in the way we work. Most of our roles are hybrid with a mix of in-office/home working and potentially adjustable working hours. Let’s discuss what works for you and AER during the interview process.
The Company is committed to the principle that no employee or job applicant shall receive unfavourable treatment on grounds of age, disability, gender reassignment, race, religion or belief, sex, sexual orientation, marriage or civil partnership, pregnancy, and maternity.
To apply, please submit your Résumé / CV, a personal summary, your salary expectations and please inform us of your notice period.
Unfortunately, we are unable to accept applications via email, telephone, or social media platforms. To be considered for this position, please submit your application using the link provided. Applications submitted through any other channel will not be reviewed.
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Senior AI Engineer in Oxford employer: Aurora Energy Research
Contact Detail:
Aurora Energy Research Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior AI Engineer in Oxford
✨Tip Number 1
Network like a pro! Reach out to folks in the AI community, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those involving large language models or RAG pipelines. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice explaining complex AI concepts in simple terms, as you'll need to communicate effectively with both technical and non-technical stakeholders.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're serious about joining our team and ready to dive into the exciting world of AI at Aurora.