Gen AI Engineer – Graph RAG on AWS, Clearance Eligible

Gen AI Engineer – Graph RAG on AWS, Clearance Eligible

Full-Time 60000 - 80000 Β£ / year (est.) No working from home possible
NTT DATA

At a Glance

  • Tasks: Deploy innovative AI solutions and collaborate with global developers on exciting projects.
  • Company: Join NTT DATA, a leader in AI technology based in Greater London.
  • Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
  • Other info: Dynamic team environment with a focus on AI ethics and data safety.
  • Why this job: Be at the forefront of generative AI and make a real impact in the tech world.
  • Qualifications: Strong background in AI solutions and AWS technologies required.

The predicted salary is between 60000 - 80000 Β£ per year.

NTT DATA in Greater London is looking for a skilled Gen AI specialist to join their Gen AI COE. The ideal candidate will have a strong background in AI solutions, specifically using AWS technologies, and a deep understanding of generative AI techniques. This role offers opportunities to work on novel projects and collaborate with global AI developers.

Responsibilities include:

  • Deploying solutions
  • Onboarding customer documents
  • Tuning AI prompts

A strong understanding of AI ethics and data safety in usage of LLMs is essential for this position.

Gen AI Engineer – Graph RAG on AWS, Clearance Eligible employer: NTT DATA

NTT DATA is an exceptional employer in Greater London, offering a dynamic work culture that fosters innovation and collaboration among AI specialists. Employees benefit from engaging in cutting-edge projects, ample opportunities for professional growth, and a commitment to ethical AI practices, making it a rewarding environment for those passionate about generative AI and AWS technologies.

NTT DATA

Contact Details:

NTT DATA Recruitment Team

StudySmarter Expert Advice🀫

We think this is how you could land Gen AI Engineer – Graph RAG on AWS, Clearance Eligible

✨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 NTT DATA!

✨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 Gen AI Engineer – Graph RAG on AWS, Clearance Eligible at NTT DATA.

✨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 NTT DATA.

✨Apply Directly through Our Website

When you find a suitable opening like Gen AI Engineer – Graph RAG on AWS, Clearance Eligible at NTT DATA, 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 Gen AI Engineer – Graph RAG on AWS, Clearance Eligible

Python
SQL
Problem-Solving Skills
Data Engineering
Communication Skills
Data Pipeline Development
API Integration

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 NTT DATA, 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 NTT DATA. 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 NTT DATA

✨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 NTT DATA!

✨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.