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For Companies At a Glance
- Tasks: Build and own ML/LLM pipelines for healthcare, ensuring data reliability and pipeline health.
- Company: Join a dynamic startup reshaping the healthcare industry with innovative tech solutions.
- Benefits: Remote work, competitive salary, and the chance to make a real impact in healthcare.
- Other info: Be part of a collaborative team tackling challenging problems in a fast-paced environment.
- Why this job: Take ownership of projects and work on cutting-edge AI technologies that matter.
- Qualifications: 7+ years in data engineering, proficient in Python, and experience with large datasets.
The predicted salary is between 70000 - 90000 £ per year.
Overview
Location: UK only | Remote Full time Permanent
Reports to: Head of Engineering
Existing Clients: Top 100 Lifesciences, MedTech and Pharma companies
Type: Full-time
Core responsibilities
- Build and own ML/LLM pipelines end-to-end: document parsing, chunking, embeddings generation, vector indexing, agentic tool calling, multi-step workflows, retries, fallbacks, and state handling.
- Write production-grade, well-tested Python that processes large volumes of data and documents reliably.
- Own pipeline health: if data is stale, broken, or wrong, it's on you.
- Work autonomously to project deadlines with minimal hand-holding.
Key qualifications & skills (non-negotiable)
- 7+ years in backend data-heavy development or data engineering
- Previously worked in Startup
- Highly proficient in Python
- Hands-on experience with large datasets and high-velocity data streams (Kafka, Flink, Spark).
- Strong with pipeline orchestration tools (Airflow, MLflow, or equivalent).
- Solid SQL skills (Postgres, BigQuery, or Snowflake) and NoSQL experience (DynamoDB, OpenSearch, Elastic).
- Real experience with LLM workflows: RAG architectures, embeddings/vector DBs, prompt engineering, function/tool calling, observability.
- Deep understanding of ETL/ELT patterns and data processing at scale.
Preferred background (strong signals)
- Experience with AWS data stack at scale.
- Exposure to healthcare, life sciences, or regulated industries.
- Built and shipped data, ML and LLM-powered pipelines in production.
- Has debugged a pipeline and knows why observability matters.
- Worked in a fast-moving startup where "that's not my job" doesn't exist.
What will get you rejected
- I set up the pipeline, someone else monitors it mindset.
- Tutorials and side projects but no production experience at scale.
- Can't explain trade-offs between streaming vs. batch, or why you chose one vector DB over another.
- Needs detailed specs before writing a line of code.
- No curiosity about healthcare or what the data actually means.
Interested? We're a distributed team solving hard problems that will reshape the healthcare industry for a generation. If you want ownership, not just tickets, we'd like to hear from you.
Senior AI & Data Engineer UK Permanent in London employer: Vamstar
Contact Detail:
Vamstar Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior AI & Data Engineer UK Permanent in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those working in healthcare or data engineering. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving ML/LLM pipelines. This gives us a taste of what you can do and makes you stand out from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge. Be ready to discuss your experience with Python, data processing, and pipeline orchestration tools. We love candidates who can dive deep into their expertise!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, we’re always on the lookout for passionate individuals who want to make a difference in healthcare.
We think you need these skills to ace Senior AI & Data Engineer UK Permanent in London
Some tips for your application 🫡
Show Off Your Experience: Make sure to highlight your 7+ years in backend data-heavy development. We want to see your journey, especially if you've worked in a startup environment. Share specific projects where you’ve built and shipped data pipelines!
Be Specific About Your Skills: When listing your skills, be clear about your proficiency in Python and your experience with tools like Kafka, Airflow, and SQL databases. We love details, so don’t just say you know them—give us examples of how you’ve used them in real-world scenarios.
Demonstrate Your Problem-Solving Mindset: We’re looking for candidates who take ownership of their work. In your application, share instances where you’ve debugged a pipeline or made decisions on trade-offs between streaming and batch processing. Show us your curiosity and problem-solving skills!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and get to know you better. Plus, it shows you’re serious about joining our team and tackling those hard problems in healthcare!
How to prepare for a job interview at Vamstar
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description. Brush up on your Python skills, especially in writing production-grade code, and be ready to discuss your experience with data-heavy development and pipeline orchestration tools like Airflow or MLflow.
✨Showcase Real-World Experience
Prepare to share specific examples from your past roles where you've built and shipped data pipelines in production. Highlight any challenges you faced and how you overcame them, especially in a startup environment where adaptability is key.
✨Understand the Healthcare Context
Since this role is focused on healthcare, do some research on the industry. Be prepared to discuss how your work impacts healthcare outcomes and why you’re passionate about using data to solve real-world problems in this field.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions that show your curiosity about the company’s projects and challenges. This not only demonstrates your interest but also helps you gauge if the company aligns with your career goals.