Senior Cloud Architect, ML/AI

TL;DR

Senior Cloud Architect, ML/AI (AWS): Lead the design and implementation of production-grade ML and Generative AI solutions on AWS with an accent on secure, reliable, cost-efficient, and observable architectures. Focus on translating complex business problems into scalable cloud systems, optimizing large-scale AI/ML workloads, and developing reusable patterns for internal and customer use.

Location: Remote in the US, Colombia, Mexico, Canada, the UK, Ireland, Estonia, Sweden, the Netherlands, and Israel. Open to contractors in Eastern Europe or Portugal.

Company

Global technology company helping cloud-driven organizations with multicloud management, specializing in Kubernetes, GenAI, CloudOps; strategic partner of AWS, Google Cloud, and Microsoft Azure serving 4,000+ customers worldwide.

What you will do

• Lead discovery, architecture, and implementation of advanced ML and Generative AI workloads on AWS, including data, training, inference, and integration.
• Act as hands-on expert and trusted advisor for customers, defining outcomes, making tradeoffs, and ensuring production-ready designs.
• Provide guidance on GenAI architectures like Amazon Bedrock, SageMaker, and integrate with existing systems.
• Drive product adoption of hirify.global Cloud Intelligence capabilities in customer engagements and measure business/technical impact.
• Capture repeatable AI/ML patterns, reference architectures, and runbooks to build practices and influence product roadmap.
• Collaborate with sales, customer success, product teams, and cloud partners like AWS.

Requirements

• 4+ years architecting, deploying, managing cloud-based AI/ML solutions including production workloads.
• Proven experience with large distributed systems on AWS.
• Advanced AWS AI/ML services: Bedrock, SageMaker (JumpStart), prompt engineering, model evaluation, agentic AI.
• ML pipelines/MLOps: SageMaker components, TensorFlow/PyTorch, distributed training, data engineering (S3, Glue, etc.), end-to-end workflows (Lambda, EKS).
• DevOps/MLOps: CI/CD, CloudWatch, governance/security/compliance, bias mitigation.
• Multi-cloud awareness (Google Cloud AI), mentoring, communication in remote global environment.

Nice to have

• BA/BS in CS/Math or equivalent; AWS/GCP AI certifications.
• RLHF, advanced fine-tuning, Hugging Face, prior ML Engineer/Data Scientist experience.
• JIRA, Agile practices.

Culture & Benefits

• Remote-first global team with flexible schedules balancing work and home life.
• Unlimited vacation, health insurance, parental leave, employee stock options, home office allowance, professional development stipend, peer recognition.
• Entrepreneurial culture focused on knowledge pursuit, fun, diversity, and inclusion.