Lead AI Engineer

Requirements

Key Responsibilities:

• Lead the design and development of AI-driven applications, particularly focusing on RAG-based chatbot solutions.
  
• Architect robust solutions leveraging Python and Java to ensure scalability, reliability, and maintainability.
  
• Deploy, manage, and scale AI applications using AWS cloud infrastructure, optimizing performance and resource utilization.
  
• Collaborate closely with cross-functional teams to understand requirements, define project scopes, and deliver solutions effectively.
  
• Mentor team members, providing guidance on best practices in software development, AI methodologies, and cloud deployments.
  
• Ensure solutions meet quality standards, including thorough testing, debugging, performance tuning, and documentation.
  
• Continuously research emerging AI technologies and methodologies to incorporate best practices and innovation into our products.
  

---

Required Qualifications:

• Bachelors or Master’s degree in Computer Science, Engineering, Data Science, Mathematics, Statistics or related fields.
  
• At least 5 years of professional experience in AI/Machine Learning engineering.
  
• Strong programming skills in Python and Java.
  
• Demonstrated hands-on experience building Retrieval-Augmented Generation (RAG)-based chatbots or similar generative AI applications.
  
• Proficiency in cloud platforms, particularly AWS, including experience with EC2, Lambda, SageMaker, DynamoDB, CloudWatch, and API Gateway.
  
• Solid understanding of AI methodologies, including natural language processing (NLP), vector databases, embedding models, and large language model integrations.
  
• Experience with leading projects or teams, managing technical deliverables, and ensuring high-quality outcomes.
  
• AWS certifications (e.g., AWS Solutions Architect, AWS Machine Learning Specialty).
  
• Familiarity with popular AI/ML frameworks and libraries such as Hugging Face Transformers, TensorFlow, PyTorch, LangChain, or similar.
  
• Experience in Agile development methodologies.
  
• Excellent communication skills, capable of conveying complex technical concepts clearly and effectively.
  
• Strong analytical and problem-solving capabilities, with the ability to navigate ambiguous technical challenges.