Job Description

We're seeking a highly skilled Cloud Engineer to design, implement, and maintain cloud infrastructure that powers AI solutions across multiple platforms/sources. This role will focus on enabling, configuring, and optimizing AI services on AWS and Google Cloud Platform (GCP), including but not limited to AWS Bedrock and Google Vertex AI. You will play a critical role in ensuring secure, scalable, and cost-efficient cloud environments for enterprise-grade AI applications.

Day to Day:

Cloud Architecture & AI Services Enablement:

• Design and implement cloud-native architectures for AI workloads across AWS and GCP.
• Configure and maintain AI services such as AWS Bedrock, Google Vertex AI, and related ML/AI offerings.
• Enable integration of LLMs and AI frameworks with enterprise data sources and APIs.
• Implement secure networking, IAM policies, and data access controls for AI services.

Automation & Optimization:

• Develop automation scripts and Infrastructure-as-Code (IaC) using tools like Terraform, CloudFormation, and Deployment Manager.
• Optimize cloud resources for performance, scalability, and cost efficiency (FinOps).
• Monitor and manage AI service usage, quotas, and billing across multi-cloud environments.

AIOps Enablement:

• Build, run, and automate AIOps capabilities to enhance observability, predictive maintenance, and intelligent incident management across cloud and AI services.
• Integrate AIOps workflows with monitoring tools and telemetry dashboards for proactive issue resolution.

Observability & Governance:

• Implement telemetry dashboards for AI service performance, compliance, and policy adherence.
• Ensure alignment with Responsible AI and enterprise governance frameworks.

Collaboration & Enablement:

• Partner with AI Engineers, ML Ops teams, and business stakeholders to operationalize AI services.
• Provide technical guidance on best practices for cloud-based AI deployments.

What do you need to succeed?

• Bachelor's degree in Computer Science, Information Systems, Engineering, or related field.
• 1-5 years of cloud engineering experience, with strong expertise in AWS and GCP.
• Hands-on experience with AI services such as AWS Bedrock, Google Vertex AI, and related ML/AI offerings.
• Proficiency in Terraform, CloudFormation, and scripting languages (Python, Bash).
• Strong understanding of IAM, VPC design, secure data access, and API integration.
• Mandatory experience in building, running, and automating AIOps workflows for cloud and AI environments.
• Familiarity with ML Ops tools, containerization (Docker, Kubernetes), and CI/CD pipelines.
• Knowledge of enterprise architecture, observability tools, and FinOps practices.
• Prior experience in media, sports, or entertainment domains is a plus.

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