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- Tasks: Design scalable data pipelines and optimise AI infrastructure using cutting-edge tech.
- Company: Join a forward-thinking company at the forefront of AI innovation.
- Benefits: Enjoy competitive pay, flexible work options, and opportunities for growth.
- Other info: Collaborative environment with endless learning and career advancement opportunities.
- Why this job: Make a real impact in the exciting world of GenAI and data engineering.
- Qualifications: Experience with PySpark, Python, and AWS services is essential.
The predicted salary is between 60000 - 80000 £ per year.
Your Responsibilities:
- Design and maintain scalable data pipelines using PySpark, Python, and distributed computing frameworks to support high‑volume data processing.
- Architect and optimize AWS-based data and AI infrastructure, ensuring secure, performant, and cost‑efficient ingestion, transformation, and storage.
- Develop, finetune, benchmark, and evaluate GenAI/LLM models, including custom training and inference optimization.
- Implement and maintain RAG pipelines, vector databases, and document-processing workflows for enterprise GenAI applications.
- Build reusable frameworks for prompt management, evaluation, and GenAI operations.
- Collaborate with cross-functional teams to integrate GenAI capabilities into production systems and ensure high-quality data, governance, and operational reliability.
Your Profile:
- Strong experience with PySpark, distributed data processing, and largescale ETL/ELT pipelines.
- Strong SQL expertise including star/snowflake schema design, indexing strategies, writing optimized queries, and implementing CDC, SCD Type 1/2/3 patterns for reliable data warehousing.
- Advanced proficiency in Python for data engineering, automation, and ML/GenAI integration.
- Hands‑on expertise with AWS services (S3, Glue, Lambda, EMR, Bedrock / custom model hosting).
- Practical experience with GenAI/LLM model creation, finetuning, benchmarking, and evaluation.
- Solid understanding of RAG architectures, embeddings, vector stores, and LLM evaluation methods.
- Experience working with structured and unstructured datasets (documents, logs, text, images).
- Familiarity with scalable data storage solutions (Delta Lake, Parquet, Redshift, DynamoDB).
- Understanding model optimization techniques (quantization, distillation, inference optimization).
- Strong capability to debug, tune, and optimize distributed systems and AI pipelines.
GenAI Engineer employer: Vallum Associates
Contact Detail:
Vallum Associates Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land GenAI Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving PySpark, AWS, and GenAI models. This gives you a chance to demonstrate your expertise beyond just words on a CV.
✨Tip Number 3
Prepare for interviews by brushing up on common technical questions related to data pipelines and GenAI. Practise explaining your thought process clearly, as communication is key when collaborating with cross-functional teams.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace GenAI Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with PySpark, AWS, and GenAI/LLM models. We want to see how your skills match the job description, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to tell us why you’re the perfect fit for the GenAI Engineer role. Share your passion for data engineering and AI, and give us a glimpse of your personality. Keep it engaging and relevant!
Showcase Your Projects: If you've worked on any cool projects involving data pipelines or GenAI, make sure to mention them! We love seeing practical examples of your work, especially if they demonstrate your problem-solving skills and creativity.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into our hands quickly. Plus, it shows us you’re genuinely interested in joining the StudySmarter team!
How to prepare for a job interview at Vallum Associates
✨Know Your Tech Inside Out
Make sure you brush up on your PySpark, Python, and AWS skills. Be ready to discuss specific projects where you've designed data pipelines or optimised infrastructure. Having concrete examples will show your expertise and help you stand out.
✨Showcase Your Problem-Solving Skills
Prepare to talk about challenges you've faced in previous roles, especially around GenAI/LLM models or distributed systems. Use the STAR method (Situation, Task, Action, Result) to structure your answers and demonstrate how you tackled those issues.
✨Understand the Company’s Needs
Research the company’s current projects and how they utilise GenAI. Tailor your responses to show how your skills can directly benefit their goals. This shows that you're not just looking for any job, but that you're genuinely interested in contributing to their success.
✨Ask Insightful Questions
Prepare thoughtful questions about their data architecture, team dynamics, or future projects. This not only shows your interest but also helps you gauge if the company is the right fit for you. Plus, it opens up a dialogue that can make you more memorable.