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Metro location and popular cloud role increase competition, but founding AI infra specialization limits applicant pool.
High domain bias due to AWS and AI-infrastructure specialization reducing cross-industry portability.
Deep AWS, infra, and AI-infrastructure requirements make candidate filtering stringent.
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Design, build, and scale the AWS cloud infrastructure for an AI-native platform from scratch without legacy constraints.
Own end-to-end systems including Infrastructure as Code, CI/CD pipelines, observability, and production reliability within a fast-moving startup environment.
Collaborate closely with Product, AI, and Engineering teams to create secure, scalable, and resilient infrastructure supporting advanced AI workloads.
Strong hands-on experience with AWS including EC2, ECS, VPC, IAM, S3, RDS, Route 53, CloudFront, CloudWatch, and Load Balancers.
Experience with Infrastructure as Code tools (Terraform preferred or AWS CloudFormation) and container technologies (Docker, CI/CD pipelines).
Knowledge of secure cloud architecture, IAM policies, secrets management, and infrastructure security best practices.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in building new cloud infrastructure for AI or ML platforms, particularly familiar with unique AI workload challenges like LLMs or vector databases.
Comfortable making independent technical decisions and owning all infrastructure aspects from architecture to automation and production reliability.
Familiarity or experience with scalable distributed systems, event-driven architectures, and hands-on experience in early-stage startup environments or 0→1 product building.