Ai Engineer (biometrics And Data Science)

AstraZeneca

Ai agents design and implementation
Prompt strategies and pipelines
Evaluation frameworks for ai
The AI Engineer will design, implement, and operationalize domain-specific AI agents, developing prompt strategies, retrieval/grounding pipelines, and guardrails

Job Summary

  • The AI Engineer will design, implement, and operationalize domain-specific AI agents, developing prompt strategies, retrieval/grounding pipelines, and guardrails.
  • You will establish robust evaluation frameworks and optimize model selection, performance, cost, and reliability for production use, collaborating closely with statistical programmers, statisticians, data scientists, and platform engineers.
  • The role involves building integrations to repositories, metadata stores, and execution environments with full provenance and traceability, and maintaining rigorous documentation to support audits.

Matching Summary

The AI Engineer will design, implement, and operationalize domain-specific AI agents, developing prompt strategies, retrieval/grounding pipelines, and guardrails.

Skills & Requirements

Must-have

  • AI agents design and implementation
  • Prompt strategies and pipelines
  • Evaluation frameworks for AI
  • Python programming and services
  • LLM integration and optimization
  • Generative AI evaluation experience

Nice-to-have

  • Domain-specific AI agents
  • Human-in-the-loop reviews
  • Regulated environments exposure
  • Vector databases and RAG techniques
  • MLOps for generative AI

Key Requirements

  • Master’s degree or equivalent practical experience
  • 3–5 years of AI/ML or NLP application experience
  • Production-grade systems with LLMs
  • Experience with prompt engineering and RAG
  • Software engineering best practices
  • Experience evaluating generative systems
  • Integrate LLMs with code generation workflows

Work Rights

Not specified

Tailored Resume

Cover Letter