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 AI/ML workloads at scale, and turning one-off solutions into reusable patterns.

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

Company

Global technology company combining data, technology, and expertise to help customers solve multicloud problems, specializing 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 for advanced ML and Generative AI workloads on AWS, including data, training, inference, and integration.
• Act as hands-on expert and trusted advisor for customers running AI/ML at scale, defining outcomes and ensuring production-ready designs.
• Provide guidance on GenAI architectures like Amazon Bedrock, SageMaker, and integrate with existing systems.
• Recommend and implement AI/ML capabilities in hirify.global Cloud Intelligence to drive product adoption and customer outcomes.
• Capture repeatable AI/ML patterns, reference architectures, and runbooks to build practice and influence product roadmap.
• Collaborate with sales, customer success, product teams, and cloud partners like AWS.

Requirements

• Remote-first global environment; must be based in specified locations: US, Colombia, Mexico, Canada, UK, Ireland, Estonia, Sweden, Netherlands, Israel (or contractors in Eastern Europe/Portugal).
• 4+ years architecting, deploying, managing cloud-based AI/ML solutions including production workloads.
• Advanced AWS proficiency for AI/ML/GenAI: Bedrock, SageMaker (JumpStart, Pipelines, Model Monitor), prompt engineering, model evaluation.
• Experience with TensorFlow, PyTorch, distributed training, data engineering (S3, Glue, Lake Formation, Redshift), end-to-end workflows (Lambda, Step Functions, EKS/Fargate).
• MLOps: CI/CD (CodePipeline), monitoring (CloudWatch), governance, security, compliance, bias mitigation.
• Multi-cloud awareness (Google Cloud AI), mentoring, communication across technical/business audiences, ownership mentality.

Nice to have

• BA/BS in CS/Math or equivalent; AWS/GCP data/AI certifications (Stanford, Coursera, etc.).
• RLHF, advanced fine-tuning, Hugging Face with AWS.
• Prior ML Engineer/Data Scientist/AI Architect in consulting/SaaS.
• 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.