At a Glance
- Tasks: Design, build, and deploy cutting-edge Generative AI systems for global clients.
- Company: Join a specialist tech consultancy leading in cloud-based AI solutions.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborative environment with exciting projects and career advancement.
- Why this job: Be at the forefront of AI innovation and make a real impact.
- Qualifications: 1-3 years experience with LLM/GenAI systems and a relevant IT degree.
The predicted salary is between 55000 - 65000 £ per year.
Lynx Recruitment are recruiting for a specialist technology consultancy delivering cloud-based AI and analytics solutions to global clients.
We are looking for an experienced AI Engineer to design, build, and deploy production-ready Generative AI systems.
Role
You will own the full lifecycle of Gen AI applications, working with LLMs, RAG architectures, and agentic frameworks to deliver scalable, business-focused solutions.
Responsibilities
- Build and deploy Gen AI and RAG systems
- Develop agentic AI workflows
- Design prompts and safety guardrails
- Implement monitoring and CI/CD pipelines
- Collaborate with clients and technical teams
Requirements
- 1-3 years deploying LLM/Gen AI systems in production
- Experience with cloud platforms
- Knowledge of RAG, vector databases, and LLM frameworks
- Git and CI/CD experience
- Experience with Lang Chain and Lang Graph
- AWS experience
- IT/Technology-related university degree (minimum 2.1)
- #J-18808-Ljbffr
Artificial Intelligence Engineer employer: Lynx Recruitment
Lynx Recruitment is an exceptional employer that fosters a collaborative and innovative work culture, ideal for Senior Software Engineers looking to make a significant impact in the tech industry. With competitive salaries, flexible working arrangements, and a strong emphasis on professional development, employees are encouraged to grow their skills and advance into leadership roles while working on cutting-edge cloud-native solutions in vibrant cities like London and Manchester.
StudySmarter Expert Advice🤫
We think this is how you could land Artificial Intelligence Engineer
✨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 Lynx Recruitment!
✨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 Artificial Intelligence Engineer at Lynx Recruitment.
✨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 Lynx Recruitment.
✨Apply Directly through Our Website
When you find a suitable opening like Artificial Intelligence Engineer at Lynx Recruitment, 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 Artificial Intelligence Engineer
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 Lynx Recruitment, 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 Lynx Recruitment. 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 Lynx Recruitment
✨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 Lynx Recruitment!
✨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.
