Chief AI Platform Engineer

Hybrid in Mexico

Cloud Native Development

Location-specific conditions & benefits*

Mexico

We are seeking a visionary and experienced Chief AI Platform Engineer to join our team.

In this role, you will be responsible for designing and deploying AI/ML infrastructure at scale, addressing critical challenges in healthcare and drug discovery. This role offers a unique chance to develop advanced platforms that empower data scientists to create transformative solutions, accelerating innovation in global healthcare.

Responsibilities

Develop and oversee infrastructure and platforms to support the deployment and monitoring of machine learning solutions in production environments
Optimize system performance and scalability to meet the needs of large-scale operations
Collaborate with data science teams to create and implement sophisticated AI/ML workflows and environments on AWS
Work closely with R&D data scientists to operationalize machine learning pipelines, algorithms, and models
Manage the complete software engineering lifecycle, from architecture and development to testing and maintenance
Lead technology projects from concept to successful execution and delivery
Upgrade the existing technology stack by integrating the latest advancements in artificial intelligence and data processing
Administer an enterprise-level platform and service, addressing customer requirements and feature requests efficiently
Adopt DevOps methodologies and implement modern tools to streamline workflows and enhance automation
Scale MLOps environments to meet production-grade standards and operational requirements
Ensure compliance with GxP standards when applicable

Requirements

A minimum of 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 managing and leading development teams
Proficiency in infrastructure-as-code tools, such as Terraform, Ansible, or CloudFormation
Expertise in Python programming, with the ability to work with additional programming languages as needed
Experience with containerization and microservices architectures, utilizing platforms such as Kubernetes or Docker
Comprehensive knowledge of Continuous Integration and Continuous Delivery pipelines, including tools like CodePipeline, CodeBuild, or CodeDeploy
Proven ability to manage large-scale enterprise platforms and address end-user feature needs
Hands-on experience with DevOps tools and practices, including Docker and Git
Understanding of GxP compliance standards
Strong analytical, communication, and problem-solving skills

Nice to have

Experience developing large-scale data processing pipelines with technologies such as Hadoop, Spark, or SQL
Proficiency with data science modeling tools and environments, including R, Python, or Jupyter Notebooks
Knowledge 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 processes

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