At a Glance
- Tasks: Build AI infrastructure and develop applications to enhance efficiency and decision-making.
- Company: Join a forward-thinking Government organisation focused on AI innovation.
- Benefits: Competitive salary, hybrid work model, and opportunities for professional growth.
- Other info: Collaborate with diverse teams and explore emerging technologies for strategic advancements.
- Why this job: Make a real impact with cutting-edge AI technologies in a dynamic environment.
- Qualifications: Experience in AI infrastructure, programming, and ethical AI practices required.
The predicted salary is between 68000 - 75000 £ per year.
Our client, a Government organisation, are expanding its Artificial Intelligence team and is currently recruiting for an AI engineer responsible for building AI development and production infrastructure, as well as developing applications and systems that help the organisation increase efficiency, reduce costs, enhance impact, and make better business decisions. The role will also support the exploration and evaluation of emerging technologies and how these can contribute to the organisational strategy.
Beyond platform ownership, you will lead the technical execution of the organisation's most advanced AI use cases, including the development of complex agentic solutions. You will architect deep integrations, establish enterprise guardrails for secure agent enablement, and design the LLMOps pipelines and orchestration frameworks required to ensure AI workloads are reliably promoted across environments to produce safe, scalable outcomes.
Skill Sets:
- Applied maths, statistics and scientific practices: You can apply analytical methods including exploratory data analysis and statistical testing to a specific data set, to reach accurate and reliable conclusions. (Skill level: Working)
- Communicating between the technical and non-technical: You can listen to the needs of the technical and business stakeholders, and interpret them. (Skill level: Practitioner)
- Data Analysis and Synthesis: You can undertake data profiling and source system analysis. (Skill level: Working)
- Data Innovation: You can understand the impact on the organisation of emerging trends in data tools, analysis techniques and data usage. (Skill level: Working)
- Data Modelling, Cleansing and Enrichment: You can build and review complex data models, ensuring adherence to standards. (Skill level: Practitioner)
- Ethics and Privacy (data science): You can show an understanding of how ethical issues fit into a wider context and can work with relevant stakeholders. (Skill level: Practitioner)
- Programming and Build (software engineering): You can use agreed standards and tools to design, code, test, correct and document moderate-to-complex programs and scripts from agreed specifications. (Skill level: Practitioner)
- Systems Integration: You can define the integration build, while co-ordinating build activities across systems. (Skill level: Practitioner)
- Testing: You can review requirements and specifications, and define test conditions. (Skill level: Working)
- Turning business problems into design: You can design systems that deal with problems spanning different business areas. (Skill level: Practitioner)
Experience:
- Strong background in designing and implementing AI infrastructure: Proficient in setting up and managing enterprise cloud environments (specifically within the Microsoft Azure ecosystem).
- Proven experience deploying AI models and developing applications: This includes hands-on experience with generative AI, retrieval-augmented generation (RAG) architectures, natural language processing (NLP) techniques, and agentic workflows.
- Demonstrated ability to explore and evaluate emerging technologies: A keen interest in staying updated with the rapid advancements in AI, LLMs, and related engineering frameworks.
- Technical collaboration and engineering excellence: Experience acting as a senior technical contributor, championing engineering best practices, and driving complex problem-solving.
- Experience in ensuring ethical AI practices: A strong understanding of data privacy regulations and ethical considerations specific to AI development.
Please apply today if you have the relevant skills and experience.
Artificial Intelligence Engineer employer: Allen Lane
As a Government organisation, we pride ourselves on fostering a collaborative and inclusive work culture that values innovation and ethical practices in Artificial Intelligence. Our employees benefit from competitive salaries, hybrid working arrangements, and ample opportunities for professional growth, all while contributing to impactful projects that enhance public services. Join us in London or Newcastle to be part of a team that is at the forefront of AI development, where your expertise will help shape the future of technology in the public sector.
StudySmarter Expert Advice🤫
We think this is how you could land Artificial Intelligence Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the AI field on LinkedIn or at local meetups. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those involving Azure and generative AI. 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 soft skills. Be ready to discuss how you've tackled complex problems and collaborated with teams. Practice makes perfect!
✨Tip Number 4
Don't forget to apply through our website! We make it easy for you to find roles that match your skills and interests. Plus, it shows you're serious about joining our team!
We think you need these skills to ace Artificial Intelligence Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the AI Engineer role. Highlight your experience with AI infrastructure, cloud environments, and any relevant projects you've worked on. We want to see how your skills match what we're looking for!
Showcase Your Projects:Include specific examples of AI models or applications you've developed. Talk about the technologies you used, the challenges you faced, and how you overcame them. This helps us understand your hands-on experience and problem-solving skills.
Be Clear and Concise:When writing your application, keep it clear and to the point. Use bullet points where possible to make it easy for us to read. We appreciate a well-structured application that gets straight to the important bits!
Apply Through Our Website:Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about us and what we do!
How to prepare for a job interview at Allen Lane
✨Know Your AI Stuff
Make sure you brush up on your knowledge of AI infrastructure, especially within the Microsoft Azure ecosystem. Be ready to discuss your experience with building robust pipelines and deploying AI models, as these are key aspects of the role.
✨Communicate Like a Pro
Since this role involves liaising between technical and non-technical stakeholders, practice explaining complex concepts in simple terms. Think about examples where you've successfully managed stakeholder expectations or facilitated difficult discussions.
✨Show Off Your Data Skills
Prepare to talk about your experience with data analysis, modelling, and integration. Have specific examples ready that demonstrate how you've ensured data quality and interoperability, as well as any innovative approaches you've taken in your previous roles.
✨Stay Ethical
Be prepared to discuss ethical considerations in AI development. Familiarise yourself with current data privacy regulations and be ready to share how you've identified and mitigated biases in your work. This shows you're not just technically savvy but also responsible.
