DoiT International

Senior Cloud Architect, ML/AI

DoiT International

full-time

Posted on:

Location Type: Remote

Location: United States

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Job Level

Senior

Tech Stack

AWSCloudDistributed SystemsPyTorchTensorflow

About the role

  • Lead the design and implementation of production-grade ML and Generative AI solutions on AWS
  • Act as a hands-on expert and trusted advisor for customers running AI/ML workloads at scale
  • Translate complex business problems into cloud architectures that are secure, reliable, cost-efficient, and observable
  • Help evolve how DoiT uses AI/ML internally and with customers by turning one-off solutions into reusable patterns
  • Lead discovery, architecture, and implementation for advanced ML and Generative AI workloads on AWS
  • Own the technical success of your engagements
  • Provide opinionated guidance on GenAI architectures
  • Partner with Account Executives, Solution Engineers, and Growth FDEs to shape and win opportunities
  • Serve as technical lead for extended POVs and CloudBuild engagements
  • Build compelling technical narratives and demos
  • Act as a named technical advisor for a portfolio of existing customers
  • Lead proactive “Get FDE”–style engagements where AI/ML expertise is needed
  • Participate in structured account-team routines
  • Recommend and implement AI/ML-related capabilities in DoiT Cloud Intelligence
  • Document and measure the business and technical impact of your work
  • Design and run service-led product adoption plays
  • Execute against delivery programs and automations
  • Maintain a high personal bar for delivery quality
  • Capture repeatable AI/ML patterns, reference architectures, and runbooks
  • Identify and validate “gravel road” solutions
  • Work with Product, R&D, and growth leaders to submit and champion these patterns
  • Contribute to the FDE Delivery vision
  • Collaborate closely with Sales, Customer Success, Product, and Business Systems Engineering
  • Communicate clearly with both technical and non-technical stakeholders
  • Work with cloud partner teams to align AI/ML initiatives to program funding

Requirements

  • 4+ years of experience architecting, deploying, and managing cloud-based AI/ML solutions
  • Proven track record designing and operating large, distributed systems on AWS
  • Advanced proficiency with AWS services relevant to AI/ML and GenAI
  • Hands-on experience with Amazon Bedrock for deploying and scaling foundation models and Generative AI workloads
  • Experience fine-tuning and deploying Large Language Models (LLMs) and multimodal AI using Amazon SageMaker
  • Strong prompt engineering skills and familiarity with rigorous model evaluation
  • Understanding of agentic capabilities and patterns for AI agents that autonomously perform tasks
  • Experience with Amazon Q Business and Amazon Q Developer
  • In-depth knowledge of Amazon SageMaker components such as Pipelines, Model Monitor, Data Wrangler, and SageMaker Clarify
  • Proficiency integrating TensorFlow, PyTorch, and other ML frameworks with SageMaker
  • Experience with distributed training and performance optimization for inference
  • Strong data-engineering skills on AWS
  • Experience building end-to-end AI/ML workflows
  • Hands-on experience with CI/CD for AI/ML using AWS CodePipeline, CodeBuild, SageMaker Pipelines
  • Proficiency in monitoring and operating AI systems using Amazon CloudWatch and SageMaker Model Monitor
  • Strong understanding of AI governance, security, and compliance on AWS
  • Familiarity with AI ethics and bias detection/mitigation
  • Working knowledge of Google Cloud AI tools
  • Proven ability to mentor peers and collaborate across Sales, CS, and Product
  • Excellent communication skills across technical and business audiences
  • Natural ownership mentality
  • Demonstrated ability to work effectively in a remote-first, global environment
Benefits
  • Unlimited Vacation
  • Flexible Working Options
  • Health Insurance
  • Parental Leave
  • Employee Stock Option Plan
  • Home Office Allowance
  • Professional Development Stipend
  • Peer Recognition Program
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
AI solutionsML solutionsGenerative AIAWSAmazon BedrockLarge Language ModelsAmazon SageMakerTensorFlowPyTorchCI/CD
Soft Skills
communicationmentoringcollaborationownership mentalitytechnical advisoryproblem-solvingleadershipcustomer engagementnarrative buildingdelivery quality