Senior Cloud Architect, ML/AI
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Job Description
Senior Cloud Architect focused on designing and implementing AI/ML solutions for global clients. Leading technical engagements and delivering high-quality cloud architectures for customer success.
Responsibilities:
- 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
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