Lead Artificial Intelligence Engineer

Role Overview

Lead AI Engineer

Key Responsibilities

• Lead and mentor a team of AI Engineers and Data Scientists, fostering innovation and growth.
• Own AI project lifecycles from design to deployment and maintenance.
• Build and optimize production-grade ML systems and pipelines (MLOps).
• Stay updated on emerging AI technologies, especially

  Generative AI

  and

  LLMs

  , and implement them in real-world applications.
• Collaborate with cross-functional teams to deliver scalable, data-driven solutions.
• Ensure engineering best practices: CI/CD, automation, documentation, and architectural excellence.
• Provide technical guidance and proactively mitigate project risks.

Requirements

• Education:

  Bachelors or Master’s in Computer Science, Data Science, AI, or related fields.

• Experience:

  5+ years in AI/ML or Data Science with a proven track record of delivering impactful data products.
• Strong expertise in

  Python

  , ML libraries (Pandas, NumPy, PyTorch, TensorFlow, Scikit-learn).
• Specialized experience in

  NLP

  (preferred) or

  Computer Vision

  .
• Experience with Generative AI, LLMs, and cloud platforms (AWS, Azure, GCP).
• Good understanding of SQL/NoSQL, web frameworks (Flask, Django, FastAPI), and containerization (Docker).
• Exposure to Big Data tools (Spark, Kafka) and ML platforms (AWS SageMaker, GCP ML Engine) is a plus.
• Excellent leadership, communication, and problem-solving skills.
• Comfortable working in Agile environments like Scrum or Kanban.