Artificial Intelligence Engineer

Job Summary

Core Responsibilities

• Design and develop AI applications from data ingestion through production inference.
• Build data pipelines for preparation, feature engineering, and model training.
• Select, train, evaluate, and optimize machine learning and deep learning models.
• Develop APIs and services for real-time and batch model use cases.
• Implement production monitoring, logging, and model performance tracking.
• Collaborate with product, data, and domain teams on business-focused AI solutions.
• Meet enterprise standards for security, scalability, and responsible AI usage.

Required AI Skill Areas

• Apply supervised and unsupervised learning, model evaluation, tuning, and validation techniques.
• Use Python, Pandas, NumPy, and SQL for data preparation and feature engineering.
• Build LLM applications using prompt design, embeddings, vector search, and RAG.
• Design scalable AI architectures and deploy models as APIs or services.
• Understand model versioning, monitoring, data drift, retraining, containerization, and cloud deployment concepts.

Technical Leadership

• Architect comprehensive machine learning solutions using TensorFlow and PyTorch.
• Serve as a machine learning subject matter expert and provide technical guidance.
• Research new machine learning technologies and integrate suitable methodologies.
• Mentor team members and conduct training sessions.
• Analyze specifications, create technical collateral, and recommend client-value initiatives.

Skills Required

• Expert proficiency in TensorFlow and PyTorch.
• Advanced knowledge of Python and SQL for data-driven solutions.
• Strong understanding of data modeling, feature engineering, and algorithm selection.
• Excellent problem-solving and technical communication skills.
• Proven experience leading technical teams and mentoring junior professionals.