Senior Cloud Architect (GenAI)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
TL;DR
Senior Cloud Architect (GenAI): Lead the design and implementation of production-grade ML and Generative AI solutions on AWS with an accent on scalability, cost-efficiency, and observability. Focus on translating complex business problems into secure cloud architectures and developing reusable patterns to influence the product roadmap.
Location: Remote Canada or LATAM (Mexico and Colombia as employees; other LATAM countries as contractors)
Company
A global technology company helping organizations leverage public cloud through the Cloud Intelligence platform.
What you will do
- Lead the design and implementation of production-grade ML and Generative AI solutions on AWS.
- Act as a hands-on expert and trusted advisor for customers running AI/ML workloads at scale.
- Convert one-off customer solutions into reusable patterns (Gravel Roads) such as Terraform modules and playbooks.
- Partner with Customer Success and Account Managers to drive product adoption and customer health.
- Optimize cloud infrastructure for cost efficiency, reliability, security, and performance.
- Provide structured technical feedback to product and engineering teams to bridge feature gaps.
Requirements
- 4+ years of experience architecting and managing cloud-based AI/ML production workloads.
- Advanced proficiency with AWS, specifically Amazon Bedrock and Amazon SageMaker.
- Strong skills in prompt engineering and rigorous model evaluation (quality, safety, performance).
- Experience with MLOps, distributed training, and data engineering using S3, Glue, and Redshift.
- Working knowledge of Google Cloud AI tools (Vertex AI) for multi-cloud architecture reasoning.
- Must be based in Canada, Mexico, Colombia, or other LATAM countries.
Nice to have
- BA/BS degree in Computer Science, Mathematics, or equivalent practical experience.
- Relevant AI/ML certifications from reputable programs (Stanford, MIT, AWS/GCP).
- Experience with RLHF, Hugging Face, and hybrid AI architectures.
- Prior experience as an ML Engineer or Data Scientist in a consulting or SaaS environment.
Culture & Benefits
- Unlimited vacation and flexible working options.
- Health insurance and parental leave.
- Employee Stock Option Plan (ESOP).
- Home office allowance and professional development stipend.
- Inclusive, remote-first global environment with a focus on entrepreneurial growth.
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