Senior Cloud Architect (ML/AI)

TL;DR

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

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 specializing in multicloud solutions, hirify.global Cloud Intelligence, with expertise in Kubernetes, GenAI, CloudOps; strategic partner of AWS, Google Cloud, Microsoft Azure serving 4,000+ customers.

What you will do

• Lead discovery, architecture, and implementation of advanced ML/GenAI workloads on AWS, including data pipelines, training, inference, and integrations.
• Act as hands-on expert and advisor for customers, defining outcomes, tradeoffs, and production-ready designs focused on security, reliability, performance, cost.
• Provide guidance on GenAI architectures like Bedrock, SageMaker, Amazon Q, and integrate with existing systems.
• Drive product adoption of hirify.global Cloud Intelligence capabilities in customer engagements and measure business/technical impact.
• Build reusable AI/ML patterns, reference architectures, and gravel roads to 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 on AWS.
• Advanced proficiency with AWS AI/ML services: Bedrock, SageMaker (JumpStart, Pipelines, Model Monitor), prompt engineering, model evaluation.
• Experience with LLMs, multimodal AI, agentic capabilities, TensorFlow, PyTorch, distributed training.
• Data engineering on AWS: S3, Glue, Lake Formation, Redshift; end-to-end workflows with Lambda, Step Functions, EKS/Fargate.
• MLOps: CI/CD (CodePipeline), monitoring (CloudWatch), governance, security, compliance, bias mitigation.
• Multi-cloud awareness (Google Cloud AI), mentoring, communication in remote-first global environment.

Nice to have

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

Culture & Benefits

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