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Senior Cloud Architect, Delivery (GenAI)

DoiT·Israel·en
RemotoTiempo completoAI & Machine LearningEnterprise SoftwareCloud Computing

Join a global forward-deployed engineering team as a Senior Cloud Architect focused on production AI/ML and GenAI solutions, cloud optimization, customer adoption, and technical product feedback. The role is remote and available to full-time employees in Israel and selected European countries; it is

Responsabilidades

  • Lead the design and implementation of production-grade ML and Generative AI solutions on AWS
  • Advise customers on AI/ML workloads at scale from discovery through deployment and optimization
  • Design secure, reliable, cost-efficient, and observable cloud architectures
  • Deliver cloud optimization sessions, architecture reviews, security assessments, reliability reviews, and performance workshops
  • Improve cloud cost efficiency, resilience, security posture, automation, and operational effectiveness
  • Resolve complex cloud engineering inquiries and support requests
  • Convert customer solutions into reusable playbooks, Terraform modules, templates, diagrams, documentation, and tooling
  • Provide product and engineering feedback based on customer usage and contribute code or features where appropriate
  • Build scripts, agent skills, and internal tools that scale cloud and AI/ML expertise
  • Share knowledge through documentation, demonstrations, office hours, training, and design reviews
  • Work as an embedded technical partner with customer success and account teams
  • Translate customer pain points into technical optimization plans and help implement lasting changes
  • Use cloud intelligence products to build analytics, allocations, insights, automations, guardrails, and policy controls
  • Integrate cloud intelligence capabilities with observability, CI/CD, and governance processes

Requisitos

  • At least 4 years of experience architecting, deploying, and managing production cloud-based AI/ML solutions
  • Proven experience designing and operating large distributed systems on AWS
  • Advanced proficiency with AWS AI/ML services and hands-on Amazon Bedrock experience
  • Experience fine-tuning and deploying LLMs and multimodal AI with Amazon SageMaker, including JumpStart
  • Strong prompt engineering and model evaluation skills covering quality, safety, and performance
  • Understanding of agentic AI patterns and integration with existing systems
  • Experience with SageMaker Pipelines, Model Monitor, Data Wrangler, and Clarify
  • Proficiency with TensorFlow, PyTorch, distributed training, and inference optimization
  • Strong AWS data-engineering experience with S3, Glue, Lake Formation, and Redshift
  • Experience building AI/ML workflows with Lambda, Step Functions, API Gateway, EKS, or Fargate
  • Hands-on CI/CD, monitoring, governance, security, and compliance for AI/ML systems
  • Knowledge of IAM, KMS, data privacy, and AI bias detection or mitigation
  • Bachelor's degree in computer science, mathematics, or a related technical field, or equivalent practical experience
  • Excellent communication skills across technical and business audiences
  • Ability to mentor peers, lead enablement sessions, and work effectively in a remote global environment

Se valora

  • Experience with reinforcement learning from human feedback, advanced fine-tuning, hybrid AI architectures, or Hugging Face
  • Experience as an ML Engineer, Data Scientist, or AI-focused Architect in consulting or SaaS
  • Additional data or AI certifications
  • Experience with Jira or similar work-tracking tools
  • Exposure to Agile practices and SaaS or cloud delivery frameworks
  • Experience with Google Cloud AI services and multi-cloud architectures

Beneficios

  • Unlimited vacation
  • Flexible working options
  • Health insurance
  • Parental leave
  • Employee stock option plan
  • Home office allowance
  • Professional development stipend
  • Peer recognition program

Compatibilidad

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