Chief AI Platform Engineer

Hybrid in Mexico

Cloud Native Development

Location-specific conditions & benefits*

Mexico

We are looking for an experienced and innovative Chief AI Platform Engineer to join our team.

6In this role, you will design and implement large-scale AI/ML infrastructure to tackle significant challenges in healthcare and drug discovery. This position provides an exceptional opportunity to build advanced platforms that enable data scientists to deliver impactful solutions, driving advancements in global healthcare technology.

Responsibilities

Design and maintain infrastructure and platforms to support the deployment and monitoring of machine learning solutions in production environments
Enhance system scalability and optimize performance to meet the demands of large-scale operations
Collaborate with data science teams to design and deploy advanced AI/ML workflows and environments on AWS
Work with R&D data scientists to operationalize machine learning models, pipelines, and algorithms
Oversee the entire software engineering lifecycle, including architecture, development, testing, and ongoing maintenance
Lead the execution of technology initiatives from concept development to successful implementation
Modernize the technology stack by integrating the latest advancements in artificial intelligence and data processing
Manage an enterprise platform and service, addressing customer requirements and feature requests effectively
Implement DevOps practices and modern tools to improve automation and streamline workflows
Scale MLOps environments to meet production-level standards and requirements
Ensure systems comply with GxP standards when necessary

Requirements

At least 7 years of experience working with AWS cloud services, including expertise in SageMaker, Athena, S3, EC2, RDS, Glue, Lambda, Step Functions, EKS, and ECS
At least 1 year of experience leading and managing development teams
Proficiency in infrastructure-as-code tools such as Terraform, Ansible, or CloudFormation
Strong programming expertise in Python, with the ability to adapt to other programming languages
Experience with containerization and microservices architectures, using platforms like Kubernetes or Docker
Extensive knowledge of Continuous Integration and Continuous Delivery pipelines, including tools like CodePipeline, CodeBuild, or CodeDeploy
Demonstrated success in managing large-scale enterprise platforms and addressing feature requirements from end users
Hands-on experience with DevOps practices and tools, including Docker and Git
Awareness of GxP compliance standards
Strong analytical, problem-solving, and communication skills

Nice to have

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

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