10 часов назад
Senior Engineer, Cloud Infrastructure (US)
110 000 - 150 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Engineer, Cloud Infrastructure (US) (Terraform/Kubernetes/LLM): Designing, provisioning, and operating enterprise client cloud environments across AWS, GCP, and Azure with an accent on infrastructure automation, secure containerized workloads, and production data pipelines. Focus on deploying LLM inference, enforcing data residency, integrating enterprise APIs, and resolving failures across multiple client environments.
Location: United States
Base compensation: $110,000–$150,000 per year
Company
is a digital-first creative agency combining creativity and technology to solve complex problems for enterprise clients and build new capabilities.
What you will do
- Assess client cloud infrastructure, data stacks, and security perimeters, then create integration plans.
- Design and provision multi-environment client infrastructure with Terraform across AWS, GCP, and Azure.
- Deploy and operate Kubernetes and Helm workloads, including ETL workers and LLM inference pods.
- Build production data integrations and pipelines with scheduling, pagination, retries, rate-limit management, and distributed processing.
- Enforce data residency and container security standards, including credential protection and hardened runtime configurations.
- Lead technical sessions with client DevOps teams, resolve infrastructure failures, mentor engineers, and document reusable implementation patterns.
Requirements
- 6+ years of cloud engineering experience with production experience in at least two of AWS, GCP, and Azure.
- Deep experience provisioning production infrastructure with Terraform.
- Production Kubernetes and Helm experience, including deployment, debugging, scaling, and security.
- Experience operating production data pipelines and distributed processing systems at scale.
- Enterprise API integration experience with OAuth 2.0, API keys, rate limiting, and API gateways.
- Experience integrating Anthropic, OpenAI, or equivalent LLM APIs into production pipelines and working directly with enterprise engineering teams.
Nice to have
- Experience with LLM inference infrastructure, marketing technology stacks, or multi-tenant client environments.
- A relevant AWS, GCP, or Azure cloud certification.
- Agency, consultancy, or product-company experience serving multiple enterprise clients.
Culture & Benefits
- Work with a global client roster including Fortune 100 companies and startups.
- Collaborate across a distributed network spanning North America, South America, Europe, and Asia.
- Contribute implementation patterns, runbooks, and integration notes to a shared engineering playbook.
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