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AI Engineer

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Role Overview

We are seeking a skilled AI Engineer to design, develop, deploy, and optimize AI-powered solutions that drive business value. The ideal candidate will have expertise in Machine Learning, Generative AI, Large Language Models (LLMs), and MLOps, with experience building scalable AI applications in cloud environments.

Technical Skills

AI & Machine Learning

  • Machine Learning
  • Deep Learning
  • NLP
  • Computer Vision
  • Generative AI
  • Large Language Models (LLMs)
  • Prompt Engineering
  • Retrieval-Augmented Generation (RAG)

Programming & Frameworks

  • Python
  • TensorFlow
  • PyTorch
  • Scikit-learn
  • LangChain
  • LangGraph
  • LlamaIndex

Cloud & MLOps

  • Vertex AI / Azure AI Services / AWS SageMaker
  • MLflow
  • Docker
  • Kubernetes
  • GitHub Actions / Azure DevOps

Databases

  • PostgreSQL
  • MongoDB
  • BigQuery
  • Pinecone
  • Weaviate
  • ChromaDB

Key Competencies

  • AI Solution Design
  • Model Development & Optimization
  • Problem Solving
  • Innovation Mindset
  • Analytical Thinking
  • Stakeholder Management
  • Communication & Collaboration

Nice to Have

  • Google Professional Machine Learning Engineer, Azure AI Engineer, or AWS ML Certification.
  • Experience building enterprise-scale AI copilots and chatbots.
  • Exposure to Responsible AI, AI Governance, and Model Explainability.
  • Experience in Retail, E-commerce, Supply Chain, or Customer Analytics domains.

Success Metrics

  • Successful deployment of scalable AI solutions.
  • Improved model accuracy, performance, and reliability.
  • Reduced deployment time through MLOps automation.
  • Increased business value through AI-driven insights and automation.
  • High stakeholder satisfaction and adoption of AI solutions.

Skills

See also

AI Engineering jobs by country — openings, pay and top skills →

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