AI Software Engineer

Merck Merck · Pharma · Central Bohemian, Czech Republic

Software Engineer to join Central AI Organization (APEX CAIO) to build production-grade AI systems. The role focuses on engineering: designing, coding, and shipping reliable software that integrates LLMs, retrieval pipelines, and AI agents into enterprise products. Responsibilities include designing and implementing backend systems and APIs, building and deploying RAG pipelines and AI agents, writing clean code, contributing to CI/CD and observability, and optimizing AI components. Requires strong Python, experience with LLMs, RAG, vector databases, and RESTful APIs.

What you'd actually do

  1. Design and implement backend systems and APIs that integrate LLMs, vector databases, and retrieval components
  2. Build, deploy, and maintain RAG pipelines and AI agents in production
  3. Write clean, testable, maintainable code following engineering best practices
  4. Contribute to CI/CD pipelines, testing, and observability of AI systems
  5. Optimize AI components for performance, reliability, and correctness

Skills

Required

  • Python
  • LLMs
  • RAG architectures
  • vector databases
  • generative AI applications
  • RESTful API development
  • CI/CD
  • testing practices
  • software delivery

Nice to have

  • AWS
  • cloud provider experience
  • Containerization
  • Docker
  • Kubernetes
  • Agile/Scrum
  • prompt engineering
  • AI evaluation frameworks
  • Bachelor's or Master's in Computer Science, Software Engineering, or a related technical discipline

What the JD emphasized

  • production-grade AI systems
  • integrates large language models, retrieval pipelines, and AI agents into enterprise products
  • strong software development fundamentals to AI-driven systems
  • production-level Python is essential
  • Hands-on experience with LLMs, RAG architectures, vector databases, or generative AI applications

Other signals

  • designing, coding, and shipping reliable software that integrates large language models, retrieval pipelines, and AI agents into enterprise products
  • Build, deploy, and maintain RAG pipelines and AI agents in production
  • Optimize AI components for performance, reliability, and correctness