AI Architect

Summary

Join our team as an AI Architect with Data Engineering expertise to design, implement, and optimize AI/ML solutions at scale. Collaborate with data engineers, scientists, and stakeholders to build intelligent systems driving business outcomes. You will lead the development of AI pipelines, ensuring data quality, security, and high availability. This role requires strong knowledge of data platforms like Snowflake and MongoDB, proficiency in Python and ML frameworks, and experience with MLOps tools. You will mentor engineering teams and stay current with emerging technologies. This is a remote contract position.

Requirements

• Proven experience as an AI/ML Architect or Senior Data Architect with exposure to AI projects
• Strong knowledge of data platforms such as Snowflake, MongoDB, PostgreSQL, Redshift, etc
• Experience with Python, SQL, and ML frameworks such as TensorFlow, PyTorch, Scikit-learn
• Solid understanding of data modeling, ETL/ELT processes, data lakes, and data warehouses
• Familiarity with MLOps tools and practices (e.g., MLflow, Kubeflow, SageMaker, Airflow)
• Excellent communication and leadership skills
• Experience with cloud platforms such as AWS, Azure, or GCP

Responsibilities

• Design and develop scalable AI/ML architectures integrated with modern data platforms (e.g., Snowflake, MongoDB)
• Collaborate with data engineers and data scientists to operationalize ML models in production environments
• Lead the development of AI pipelines, model training, validation, deployment, and monitoring
• Architect data workflows that ensure data quality, security, and high availability
• Identify opportunities to apply AI/ML to business challenges and drive PoCs and pilot projects
• Ensure architecture aligns with enterprise standards and compliance requirements
• Mentor engineering teams and provide architectural guidance on AI and data solutions
• Stay current with emerging technologies and trends in AI, machine learning, and data systems

Preferred Qualifications

• Master's or Ph.D. in Computer Science, Data Science, AI, or a related field
• Certifications in AI/ML or cloud architecture (e.g., AWS Certified Machine Learning, Snowflake SnowPro)
• Experience in designing real-time AI systems and streaming data solutions (e.g., Kafka, Flink)