D
Senior Cloud Architect, Delivery (GenAI)
RemoteFull-timeAI & 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
Responsibilities
- 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
Requirements
- 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
Nice to have
- 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
Benefits
- Unlimited vacation
- Flexible working options
- Health insurance
- Parental leave
- Employee stock option plan
- Home office allowance
- Professional development stipend
- Peer recognition program