Manager, AI Engineer

Merck Merck · Pharma · Telangana, India

Manager for an AI Engineering team focused on building and deploying AI solutions on cloud platforms, utilizing ML, LLMs, and RAG. The role involves people management, technical leadership in software engineering, MLOps, and cloud infrastructure, with a focus on delivering scalable and reliable AI solutions for healthcare business problems.

What you'd actually do

  1. Collaborate with global stakeholders and partners to evaluate value of AI engineering projects.
  2. Act as people manager and mentor to junior and mid-level engineers, driving best practices in platform engineering, software development, infrastructure management, and DevOps methodologies.
  3. Overlook team writing efficient, maintainable, and secure code following software engineering best practices.
  4. Design and deliver backend, front end services and AI platform components with high scalability and reliability.
  5. Architect, deploy, and operate cloud-native infrastructure (primarily AWS or GCP).

Skills

Required

  • DevOps
  • Machine Learning (ML)
  • Software Development
  • Python
  • MLOps practices
  • large language models (LLMs)
  • retrieval-augmented generation (RAG)
  • cloud-native infrastructure (AWS or GCP)
  • Infrastructure-as-Code
  • containerization
  • Kubernetes
  • CI/CD pipelines (GitHub Actions, Argo CD)
  • Git
  • Docker
  • observability

Nice to have

  • Amazon Web Services (AWS)
  • JavaScript
  • Agile methodology
  • AWS certified
  • Java
  • TypeScript
  • .NET

What the JD emphasized

  • AI engineering
  • people management experience
  • hands-on Python skills
  • Proven experience building scalable AI solutions
  • Solid understanding of machine learning and GenAI concepts
  • Experience with DevOps practices

Other signals

  • AI Engineering Manager
  • build, manage and develop a team of 3-4 AI, cloud and full stack engineers
  • design and building of AI solutions operated on cloud-based platforms
  • programming (such as Python), modern software engineering, MLOps practices, machine learning, large language models (LLMs), retrieval-augmented generation (RAG)