At a Glance
- Tasks: Build and deploy AI solutions while collaborating with clients on innovative projects.
- Company: Join Talan Data x AI, a leading consultancy in data management and analytics.
- Benefits: Enjoy competitive salary, 25 days holiday, private medical insurance, and professional development opportunities.
- Other info: Dynamic consulting role with clear leadership growth path and exposure to real client challenges.
- Why this job: Make a real impact in AI and machine learning from day one with genuine responsibility.
- Qualifications: 2-4 years in data science or AI engineering, strong Python skills, and team collaboration experience.
The predicted salary is between 29500 - 42000 £ per year.
Requirements
- Typically, 2–4 years experience in data science, machine learning, or AI engineering.
- Solid grounding in core data science and machine learning.
- Practical experience with LLMs and generative AI, including prompting and RAG.
- Familiarity with how AI agents are built and orchestrated.
- Strong Python skills and experience with common data and machine learning libraries.
- Good engineering habits.
- Clear communication skills and a collaborative team mindset.
- Willingness to work on client sites, potentially for extended periods.
- Willingness to travel for work purposes and stay away from home for extended periods.
- Eligibility to work in the UK without restriction.
- Exposure to cloud AI platforms, with Azure as a plus.
- Experience practicing MLOps and LLMOps.
- Early experience mentoring junior colleagues.
- Interest in consulting and client-facing delivery.
Responsibilities
- Build, test, and deploy AI and machine learning components within client projects to the standards and designs set by senior colleagues.
- Develop Gen AI and LLM-based features, including prompting, retrieval-augmented generation, and simple agentic workflows, alongside more traditional ML models.
- Deliver classical data science tasks such as data preparation, feature engineering, model training, and evaluation.
- Translate solution designs into clean, well-documented, production-minded code.
- Contribute to model evaluation, testing, and monitoring.
- Support and guide very junior and graduate resources, reviewing their work and helping them grow.
- Help peers unblock technical problems and share knowledge across the team.
- Take part in client and team discussions and communicate work clearly.
Technologies
- AI
- AI Agents
- Azure
- Cloud
- Support
- LLM
- Machine Learning
- MLOps
- Model Training
- Python
- RAG
More
We are Talan Data x AI, a leading Data Management and Analytics consultancy working closely with leading software vendors and top industry experts across a range of sectors to unlock value and insight from data.
Innovation is at the heart of our client offerings, and we help companies improve efficiency with modern processes and technologies such as Machine Learning and Artificial Intelligence.
This is a full-time consulting role at associate level, focused on delivery across modern AI and offering genuine responsibility from day one, exposure to real client problems, and a clear path into a leadership track.
Our compensation and benefits package includes BDP Plus, 25 days holiday plus bank holidays, a 5-day holiday buy/sell option, private medical insurance, life cover, cycle to work scheme, eligibility for our pension scheme with a 5% employer contribution and salary sacrifice option, an employee assistance programme, and bespoke online learning via Udemy for Business.
- last updated 36 week of 2026
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AI Engineer (LLMs, Agents & Data Science) employer: Talan
Talan is an excellent employer for those passionate about smart energy solutions, offering a collaborative work culture that prioritises innovation and professional growth. Located in the heart of GB, employees benefit from engaging with industry experts and contributing to impactful projects that enhance energy security and privacy. With a strong commitment to employee development and a focus on meaningful work, Talan provides a rewarding environment for Smart Energy Analysts looking to make a difference.
StudySmarter Expert Advice🤫
We think this is how you could land AI Engineer (LLMs, Agents & Data Science)
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Talan!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like AI Engineer (LLMs, Agents & Data Science) at Talan.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Talan.
✨Apply Directly through Our Website
When you find a suitable opening like AI Engineer (LLMs, Agents & Data Science) at Talan, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace AI Engineer (LLMs, Agents & Data Science)
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 Talan, 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 Talan. 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 Talan
✨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 Talan!
✨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.
