Description

You will lead the design and implementation of production-grade AI solutions on AWS, owning the full lifecycle from architecture to MLOps pipelines.

This role is on-site.

Responsibilities

• Design and build scalable, secure AI systems using AWS services like SageMaker, Bedrock, and Glue.
• Develop and maintain MLOps pipelines, ensuring robust model optimization and deployment.
• Lead code reviews, enforce engineering standards, and mentor teams on best practices.
• Translate technical concepts into business value for executive stakeholders and customers.
• Ensure all AI solutions meet performance, scalability, and compliance requirements.

Required Skills

• 10+ years of experience in AI/ML, data engineering, or cloud architecture.
• Strong hands-on proficiency with Python, SQL, and ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Deep understanding of ML algorithms, LLMs, embeddings, vector search, and model optimization.
• Experience with Infrastructure as Code tools: AWS CDK, Terraform, and CloudFormation.
• Proven track record of building production-grade MLOps pipelines.
• Strong knowledge of software engineering principles, design patterns, and testing practices.

Preferred Skills

• Experience in consulting, customer advisory, or enterprise architecture roles.
• Ability to engage technical and executive stakeholders effectively.

Key Skills

Education

Bachelor's degree