Hybrid AWS Cloud Engineer

at EXL

• Job title: AWS Cloud Engineer
• Job type: Full Time
• Experience level: Mid level, Senior
• Salary: Not specified
• Degree requirement: Bachelor's Degree
• Tech skills: Airflow, AWS, Cloud, Docker, Grafana, Jenkins, Kubernetes, Prometheus, Python, Ray, Spark, Terraform
• Location requirements: Hybrid, Colombia

About the role

• AWS Cloud Engineer optimizing AWS environments for data science workloads. Collaborating with data and ML teams on cloud architecture and ML infrastructure.

Responsibilities

• Manage, scale, and optimize cloud environments used for data science workloads (primarily AWS, Databricks, dbt).
• Provision, maintain, and optimize compute clusters for ML workloads (e.g., Kubernetes, ECS/EKS, Databricks, SageMaker).
• Implement and maintain high-availability solutions for mission-critical analytics platforms.
• Deep expertise in AWS resource management and provisioning, including IAM roles and permissions.
• Develop CI/CD pipelines for model deployment, infrastructure-as-code (IaC), and automated testing using industry standard toolchains.
• Build monitoring, alerting, and logging systems for cloud and ML infrastructure (e.g., Datadog, CloudWatch, Prometheus, Grafana, ELK).
• Automate provisioning, configuration, and deployments using tools such as Terraform and CloudFormation, GitHub actions, etc.
• Implement and operationalize data science security and compliance controls for data science platforms in alignment with enterprise cloud standards.
• Conduct periodic risk assessments, best practice reviews, and remediation efforts to strengthen security and resiliency.
• Support secure handling of sensitive financial data.
• Partner with data scientists, machine learning engineers, and data engineers to deeply understand and support their needs and workflows within data-driven initiatives.
• Serve as a technical advisor on cloud architecture, performance optimization, and production readiness for data and ML platforms.
• Adopt and champion Agile, DevOps, and Platform Engineering practices (kanban, scrum, continuous improvement, automation, Everything-as-a-Service).
• Demonstrate a strong, proactive focus on serving internal customers, prioritizing user experience, identifying opportunities to leverage automation and self-service to reduce toil and cognitive load for developers and researchers.

Requirements

• A bachelor’s degree or higher in a STEM field, required
• 5+ years of experience in cloud operations, DevOps, platform engineering, SRE, sysadmin or related roles.
• Strong proficiency with at least one major cloud provider (AWS preferred).
• Hands-on experience with IaC tools (Terraform, CloudFormation, or similar).
• Strong scripting skills (Python, Bash, or PowerShell).
• Strong understanding of modern authentication and authorization technologies and secrets management (IAM, OIDC, OAuth2, RBAC, ABAC, privileged access management, JIT authorization, PKI).
• Experience with common CI/CD systems (GitHub Actions, Jenkins, GitLab CI, ArgoCD,, or similar).
• Familiarity with container orchestration (Docker Compose, EKS/Kubernetes, ECS).
• Experience supporting data-intensive or ML workloads.
• Experience in financial services, investment management, or other highly regulated industries preferred.
• Knowledge of ML/AI platform tools (Databricks, SageMaker, MLflow, Airflow) preferred.
• Hands-on experience with AI Engineering and LLMOps tools (LLM observability, eval pipelines, building/supporting agentic workflows) are a huge plus.
• Understanding of networking, VPC architectures, and cloud security best practices preferred.
• Familiarity with distributed compute frameworks (Spark, Ray, Dask) preferred.

Benefits

• EXL never requires or asks for fees/payments or credit card or bank details during any phase of the recruitment or hiring process
• EXL will only extend a job offer after a candidate has gone through a formal interview process with members of EXL’s Human Resources team, as well as our hiring managers.