At a Glance
- Tasks: Lead the design of next-gen AI solutions for large-scale data transformations.
- Company: Join UST, a global tech organisation with a focus on innovation.
- Benefits: Competitive salary, career progression, and a collaborative work environment.
- Other info: Work on cutting-edge projects in a dynamic and supportive team.
- Why this job: Shape the future of AI and make a real impact in data engineering.
- Qualifications: Expertise in AI architectures, Python, and data engineering concepts required.
The predicted salary is between 80000 - 98000 £ per year.
We are seeking a highly skilled AI Engineering Architect to lead the design and development of next‑generation Agentic AI solutions powering large‑scale data transformations.
Location: London / Nottingham
Employment Type: Full‑time
Company: UST
This role acts as the “brain” of a transformation accelerator, driving intelligent automation across complex data pipelines using advanced LLM frameworks and AI‑driven engineering practices.
Key Responsibilities
- Architect and implement Agentic AI workflows to automate:
- Legacy pipeline parsing
- PySpark code generation
- DAG (workflow) generation
- Design and standardize:
- Prompt engineering frameworks
- Context management strategies for LLMs
- Build and enhance:
- AI validation pipelines (including hallucination detection and control)
- Static analysis mechanisms for generated code
- Enable enterprise‑scale AI adoption by:
- Driving AI‑generated documentation and metadata
- Scaling intelligent automation across thousands of pipelines
Required Skills & Experience
- Strong expertise in:
- Agentic AI / LLM architectures / prompt engineering
- Python development
- Data engineering concepts (for validation and automation workflows)
- Proven experience designing AI‑driven automation solutions
- Ability to develop scalable frameworks for AI code generation and validation
Nice to Have
- Experience with orchestration frameworks (e.g., Airflow or similar)
- Exposure to data processing frameworks such as PySpark
What We Offer
- Opportunity to work on cutting‑edge Agentic AI transformation programs
- High‑impact role shaping enterprise‑scale AI adoption
- Collaborative and innovation‑focused environment
- Career progression within a global technology organisation
If you’re passionate about building intelligent systems that transform how data platforms are designed and delivered, we’d love to hear from you.
AI Engineering Architect -Agentic AI & Data Platforms(Data Architect II) in Nottingham employer: UST
UST is an exceptional employer, offering a dynamic and collaborative work culture that fosters innovation and creativity in the field of AI engineering. With opportunities for career progression within a global technology organisation, employees can engage in high-impact projects that shape enterprise-scale AI adoption while working in vibrant locations like London and Nottingham. The company prioritises employee growth and provides a supportive environment for those passionate about transforming data platforms through cutting-edge technology.
StudySmarter Expert Advice🤫
We think this is how you could land AI Engineering Architect -Agentic AI & Data Platforms(Data Architect II) in Nottingham
✨Get Involved in Data Science Meetups
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We think you need these skills to ace AI Engineering Architect -Agentic AI & Data Platforms(Data Architect II) in Nottingham
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at UST, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at UST. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at UST
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at UST!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
