Senior AI and Data Engineer for Healthcare

vamstar • United Kingdom
Remote
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AI Summary

Design, build, and maintain data pipelines and ML/LLM pipelines for top healthcare companies. Requires 7+ years of backend data-heavy development experience and proficiency in Python, SQL, and NoSQL.

Key Highlights
Design and maintain data pipelines
Build and own ML/LLM pipelines
Work autonomously with minimal hand-holding
Key Responsibilities
Design, build, and maintain batch/streaming data pipelines
Build and own ML/LLM pipelines end-to-end
Write production-grade, well-tested Python that processes large volumes of data and documents reliably
Technical Skills Required
Python SQL NoSQL Kafka Flink Spark Airflow MLflow Postgres BigQuery Snowflake DynamoDB OpenSearch Elastic LLM workflows RAG architectures embeddings/vector DBs prompt engineering function/tool calling observability
Benefits & Perks
Full-time
Permanent
Remote work
UK only
Nice to Have
Experience with AWS data stack at scale
Exposure to healthcare, life sciences, or regulated industries

Job Description


Title: Senior AI & Data Engineer - Healthcare AI

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 & objectives

  • Design, build, and maintain batch/streaming data pipelines, ingestion, cleaning, normalisation, enrichment, deduplication.
  • 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.


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