At a Glance
- Tasks: Design and build AI-powered applications that tackle real business challenges.
- Company: Join a forward-thinking company focused on innovative AI solutions.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on continuous learning and career advancement.
- Why this job: Make a tangible impact by enhancing AI capabilities and improving decision-making processes.
- Qualifications: Strong Python skills and experience in developing production-grade AI applications.
The predicted salary is between 80100 - 97900 £ per year.
Our client is seeking a pragmatic, hands-on Data & AI Engineer to design, build, and operate AI-powered applications and agents that solve real business problems. You'll join our client's team to enhance existing AI solutions, create new AI capabilities that improve workflows and decision-making, and work closely with business stakeholders and engineers to embed domain expertise into robust, production-grade AI systems.
Key Skills & Experience
- Python software development - Strong, production-level coding skills to build reliable, maintainable AI services.
- End-to-end software delivery - Experience designing, building, testing, deploying, and operating production-grade systems.
- AI/LLM application development - Hands-on experience creating AI or LLM-based applications used by real users, not just experimenting with consumer tools.
- AI system lifecycle - Exposure to prototyping, data preparation, evaluation, deployment, monitoring, and continuous improvement of AI systems.
- AI evaluation and metrics - Ability to design and run evaluations, and measure model/agent quality, reliability, safety, and business impact.
- Working with multiple model providers - Understanding of different model families, trade-offs in latency, cost, context limits, and deployment constraints.
- Prompt and agent design - Experience treating prompts and agent instructions as versioned, testable software artifacts.
- Systems integration - Integrating AI with APIs, enterprise applications, data platforms, and both structured and unstructured data.
- Advanced AI techniques - Familiarity with retrieval-augmented generation, tool calling, structured outputs, agent orchestration, and workflow automation.
- Model adaptation foundations - Understanding when to use prompting, retrieval, fine-tuning, and how to prepare and evaluate data and models for post-training.
- Business and data understanding - Ability to grasp complex workflows, rules, and processes, and translate them into AI-enabled solutions.
Data & AI Engineer in London employer: Annapurna
Annapurna is an exceptional employer, offering a dynamic work culture that prioritises professional growth and development. As a Learning & Leadership Partner in London, you will have the unique opportunity to influence the leadership landscape within a high-growth fintech environment, while enjoying a supportive atmosphere that fosters collaboration and innovation.
StudySmarter Expert Advice🤫
We think this is how you could land Data & AI Engineer in London
✨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 Annapurna!
✨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 Data & AI Engineer at Annapurna.
✨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 Annapurna.
✨Apply Directly through Our Website
When you find a suitable opening like Data & AI Engineer at Annapurna, 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 Data & AI Engineer in London
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 Annapurna, 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 Annapurna. 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 Annapurna
✨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 Annapurna!
✨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.
