Artificial Intelligence Engineer

Responsibilities:

Design and develop production-grade AI and machine learning models for real-world applications (e.g., recommendation engines, NLP, computer vision, forecasting).

Lead model lifecycle management from experimentation and prototyping to deployment and monitoring.

Collaborate with cross-functional teams (product, data engineering, MLOps, and business) to define AI-driven features and services.

Perform feature engineering, data wrangling, and exploratory data analysis on large-scale structured and unstructured datasets.

Build and maintain scalable AI infrastructure using cloud services (AWS, Azure, GCP) and MLOps best practices.

Mentor junior AI engineers, guiding them in model development, evaluation, and deployment.

Continuously improve model performance by leveraging new research, retraining on new data, and optimizing pipelines.

Stay current with the latest developments in AI, machine learning, and deep learning through research, conferences, and publications.

Requirements

• Bachelors or Masters degree in Computer Science, Data Science, Machine Learning or related field.
• 10+ years of IT experience with a minimum of 6+ years of AI
• Experience in AI engineering, particularly with building LLM-based applications and prompt-driven architectures.
• Solid understanding of Retrieval-Augmented Generation (RAG) patterns and vector databases (especially Qdrant).
• Hands-on experience in deploying and managing containerized services in AWS ECS and using CloudWatch for logs and diagnostics.
• Familiarity with AWS Bedrock and working with foundation models through its managed services.