Lead AI Platform Engineer

Hybrid in Mexico

Cloud Native Development

Location-specific conditions & benefits*

Mexico

We are looking for an experienced and driven Lead AI Platform Engineer to join our team.

In this role, you will be responsible for designing and deploying large-scale AI/ML infrastructure to address complex challenges in healthcare and drug discovery. This is a unique opportunity to develop state-of-the-art platforms and systems that enable data scientists to create impactful solutions, advancing global healthcare initiatives.

Responsibilities

Build and maintain infrastructure and platforms to support the deployment and monitoring of machine learning solutions in production environments
Optimize system performance and scalability to meet the demands of large-scale operations
Collaborate with data science teams to design and implement AI/ML workflows and environments on AWS
Partner with R&D data scientists to operationalize machine learning models, pipelines, and algorithms
Take responsibility for the full software engineering lifecycle, including architecture, development, testing, and maintenance
Lead technology initiatives from initial concept through successful delivery
Enhance the existing technology stack by integrating advancements in artificial intelligence and data processing
Manage an enterprise-level platform and service, addressing customer needs and feature requests
Implement DevOps practices and modern tools to improve automation and efficiency
Scale MLOps environments to production-level standards
Ensure compliance with GxP standards when applicable

Requirements

At least 5 years of experience working with AWS cloud environments, including expertise in services such as SageMaker, Athena, S3, EC2, RDS, Glue, Lambda, Step Functions, EKS, and ECS
Proficiency in infrastructure-as-code tools such as Terraform, Ansible, or CloudFormation
Strong programming expertise, particularly in Python, with consideration for other programming capabilities
Experience with containerization, microservices architectures, and platforms like Kubernetes or Docker
Advanced knowledge of Continuous Integration and Continuous Delivery pipelines, including tools like CodePipeline, CodeBuild, or CodeDeploy
Proven experience managing large-scale enterprise platforms and addressing end-user feature requests
Hands-on experience with DevOps practices and tools, including Docker and Git
Knowledge of GxP compliance standards
Strong analytical, communication, and problem-solving skills

Nice to have

Experience building large-scale data processing systems using technologies like Hadoop, Spark, or SQL
Proficiency with data science modeling tools and environments such as R, Python, or Jupyter Notebooks
Understanding of multi-cloud platforms, including AWS, Azure, and GCP
Experience mentoring and supporting team members or clients in a professional setting
Familiarity with SAFe Agile methodologies and practices

We offer/Benefits

International projects with top brands
Work with global teams of highly skilled, diverse peers
Healthcare benefits
Employee financial programs
Paid time off and sick leave
Upskilling, reskilling and certification courses
Unlimited access to the LinkedIn Learning library and 22,000+ courses
Global career opportunities
Volunteer and community involvement opportunities
EPAM Employee Groups
Award-winning culture recognized by Glassdoor, Newsweek and LinkedIn