Title: Sr. Infrastructure Engineer-AWS cloud/Terraform, AI/ML
Location: Orlando, Florida 4 days onsite and eventually 2 days onsite.
Duration: up to 14 months with possible extensions.
Compensation: 85-88/hr
Work Requirements: US Citizen, GC Holders or Authorized to Work in the U.S.
Sr. Software Engineer
The Decision Science + Integration (DDSI) team supports clients yield management, revenue planning, forecasting, pricing, and optimization. Key partners include Marketing, Finance, Business Development, Research, and Operations. Roles within the client develop, analyze, and execute strategies to maximize profitability and improve the value proposition for our Members, and Shareholders. The team leverages technology, data analytics, optimization, statistical and econometric modeling to explore opportunities, shape business decisions, and drive business value.
Candidates should have a natural curiosity to understand the "why" behind business performance, take a proactive role in problem-solving, be results oriented, be able to prioritize and be a team player in a collaborative environment.
The APS team is seeking a Senior Infrastructure Engineer to evolve the cloud infrastructure that powers analytical systems, optimization engines, and ML pipelines across The Walt Disney Company. You'll design scalable architectures for data-intensive workloads, define infrastructure standards through Terraform, and ensure the reliability and cost-efficiency of systems that directly drive business decisions. This role requires a strong computing background, a systems mindset, and the ability to deliver creative solutions to complex problems.
Basic Qualification:
our Role:
• Manage AWS cloud environments, including compute, networking, data, and security
• Design and provision infrastructure for analytical and ML workloads using Terraform
• Define and enforce infrastructure standards, patterns, and best practices across the team
• Troubleshoot production issues and drive incident resolution
• Monitor system health, define SLOs, and maintain observability across services
• Manage cloud costs — right-size resources, identify waste, and implement cost-optimization strategies
• Design and maintain network architecture including VPCs, subnets, and security groups
• Partner with developers to deploy and operationalize custom analytic applications
• Partner with Decision Science team to design and deploy data science advancements into end-to-end solutions
• Partner with Data Engineering team to establish scalable, efficient, and automated data processes
Job Requirements:
• Minimum of 5 years of experience in cloud infrastructure and systems engineering
• Strong experience managing AWS environments in production
• Experience with Infrastructure as Code practices and tooling (Terraform required)
• Experience with serverless architectures and container technologies (Docker, Kubernetes)
• Strong Linux administration skills
• Proficiency with DevOps and CI/CD tooling (GitLab, Airflow, or similar)
• Experience with observability — monitoring, logging, alerting, and SLO-based reliability practices
• Understanding of AWS networking — VPCs, subnets, security groups, load balancers, and DNS
• Experience with IAM design, security best practices, and least-privilege access patterns
• Familiarity with AI/ML concepts and comfort using AI-assisted tools in day-to-day workflows (e.g., code generation, troubleshooting, documentation)
• Experience with relational databases such as MySQL, MariaDB, or PostgreSQL
• Experience working with complex and large volumes of data and the impacts on infrastructure
• Strong written and verbal communication skills with the ability to work cross-functionally with technical and non-technical teams
Preferred Qualifications:
How To Stand Out:
• Deep Terraform expertise — module development, state management, and CI-driven plan/apply workflows
• Experience with AWS AI/ML services (Bedrock, SageMaker, or similar)
• AWS Certified Solutions Architect (Associate or Professional)
• Experience with cloud cost optimization and FinOps practices
• Experience with observability platforms (Datadog, New Relic, or CloudWatch)
• Experience with Snowflake cloud data warehouse
• Experience with non-relational, NoSQL, and semi-structured databases
• Experience creating application and network architecture diagrams
• Understanding of data science concepts and experience supporting ML workloads
• Experience with Azure or GCP in addition to AWS (multi-cloud awareness)
• Experience with entertainment, media, or related industries
Required Education:
BA/BS Degree Comp Sci/IS or related field
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