Job Description- Lead AI Engineer

Position Summary

We are seeking a Lead AI Engineer to design, develop, and deploy AI and Machine Learning solutions that drive business value. The ideal candidate will provide technical leadership, guide AI strategy, mentor engineering teams, and build scalable AI systems using modern machine learning, generative AI, and cloud technologies.

Key Responsibilities

• Lead the design, development, and deployment of AI/ML solutions across business functions.
• Define AI architecture, technical standards, and best practices.
• Develop and optimize machine learning, deep learning, and generative AI models.
• Build scalable AI pipelines for data preparation, model training, evaluation, and deployment.
• Collaborate with product, engineering, data, and business stakeholders to identify AI opportunities.
• Implement MLOps practices for model monitoring, governance, and lifecycle management.
• Evaluate emerging AI technologies and recommend adoption strategies.
• Ensure AI solutions meet security, privacy, compliance, and ethical AI standards.
• Lead technical design reviews and provide mentorship to AI/ML engineers and data scientists.
• Drive innovation and contribute to the organization's AI roadmap.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.
• 8+ years of experience in software engineering, data science, or AI/ML development.
• 3+ years of experience leading AI initiatives or engineering teams.
• Strong programming skills in Python.
• Hands-on experience with machine learning and deep learning frameworks such as:
  • TensorFlow
  • PyTorch
• Experience with Generative AI, Large Language Models (LLMs), prompt engineering, and Retrieval-Augmented Generation (RAG).
• Strong understanding of data structures, algorithms, and software engineering principles.
• Experience with cloud platforms such as:
  • Microsoft Azure
  • Amazon Web Services
  • Google Cloud
• Experience deploying AI models in production environments.

Preferred Qualifications

• Experience with MLOps tools and model lifecycle management.
• Knowledge of vector databases and semantic search technologies.
• Experience building AI agents, copilots, or conversational AI applications.
• Familiarity with containerization and orchestration technologies.
• Cloud AI certifications and relevant industry certifications.