At a Glance
- Tasks: Develop and enhance AI learning libraries while collaborating with enterprise customers.
- Company: Innovative AI company backed by tier-one VC, focused on transforming enterprise knowledge.
- Benefits: Competitive salary up to £160k, meaningful equity, and a chance to shape company culture.
- Other info: Work in a dynamic London office with opportunities for professional growth.
- Why this job: Join a small team where your contributions have lasting impact and real ownership.
- Qualifications: 3+ years in production LLM systems, strong Python skills, and experience with agentic systems.
The predicted salary is between 140000 - 160000 £ per year.
We're working with a team who spent years embedded inside some of the world's largest enterprises, deploying AI at scale before most companies had figured out what to do with it. They left to solve the problem they kept running into. The short version: enterprise AI keeps failing because the knowledge agents need to operate doesn't exist anywhere in a written form. It lives in people's heads. My client has built a platform that changes that - it learns how a business actually runs, structures that knowledge into something agents can act on, and improves every time a human makes a decision inside it. Tier-one VC backing, real enterprise customers, every pilot converted since launch.
The role: You'll be close to the core of what they're building - working directly on their learning library, shipping features with customers, and feeding what you learn back into the platform. Small team, high bar, genuine ownership. The kind of place where your architectural decisions are still visible three years later.
Day to day: agentic workflows, eval frameworks, confidence scoring, human-in-the-loop feedback loops, knowledge base agents, async orchestration infrastructure.
Who they're looking for:
- Production LLM systems with real depth behind them - not just shipped, but understood
- Agentic systems and multi-agent orchestration experience
- Comfortable sitting between research and production
- Happy working directly with enterprise customers
- 3+ years experience. Python as your main language
Why it's worth a conversation: Early enough to shape the culture. Proven enough to back it with confidence - tier-one backing, real enterprise customers, and a founding team with a track record of doing this at scale. Meaningful equity. The kind of early-stage role that doesn't feel like a gamble. London, five days on-site. Up to £160k depending on experience.
Drop me a message if it sounds interesting, and I'll tell you more.
Applied AI Engineer in London employer: Plan:it
Join a pioneering team in London that is redefining enterprise AI with a culture of innovation and genuine ownership. As an Applied AI Engineer, you'll have the opportunity to shape the future of the platform while working closely with enterprise customers, all backed by tier-one VC funding and a proven track record. With meaningful equity and a collaborative environment, this role offers not just a job, but a chance to make a significant impact in the AI landscape.
StudySmarter Expert Advice🤫
We think this is how you could land Applied 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 Plan:it!
✨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 Applied AI Engineer at Plan:it.
✨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 Plan:it.
✨Apply Directly through Our Website
When you find a suitable opening like Applied AI Engineer at Plan:it, 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 Applied 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 Plan:it, 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 Plan:it. 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 Plan:it
✨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 Plan:it!
✨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.
