Senior Cloud Architect, Delivery – GenAI

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DoiT International

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2014

☁️ SaaS

💼 Consulting

SaaS • Cloud Services • Consulting

DoiT International is a cloud services company that provides comprehensive solutions for managing and optimizing cloud infrastructure across multiple platforms such as AWS, Google Cloud, and Microsoft Azure. Their services include cloud cost management, workload intelligence, automation, and consulting. DoiT International helps businesses optimize their cloud environments, improve performance, and enhance security through a combination of advanced technology and expert consulting.

📋 Description

• Lead the design and implementation of production-grade ML and Generative AI solutions on AWS (with awareness of multi-cloud environments). • Act as a hands-on expert and trusted advisor for customers running AI/ML workloads at scale, from initial discovery through deployment and optimization. • 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 and “gravel roads” that influence the product roadmap. • Focus more on install base health, product adoption, proactive engagements, and account-team work.

🎯 Requirements

• 4+ years of experience architecting, deploying, and managing cloud-based AI/ML solutions, including production workloads. • Proven track record designing and operating large, distributed systems on AWS, selecting appropriate services and patterns to meet business and technical goals. • 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 (including JumpStart). • Strong prompt engineering skills and familiarity with rigorous model evaluation (quality, safety, performance). • Understanding of agentic capabilities and patterns for AI agents that autonomously perform tasks and integrate with existing systems. • Experience with Amazon Q Business and Amazon Q Developer (or similar tools) to accelerate insight generation and development workflows. • In-depth knowledge of Amazon SageMaker components such as Pipelines, Model Monitor, Data Wrangler, and SageMaker Clarify for bias detection and interpretability. • Proficiency integrating TensorFlow, PyTorch, and other ML frameworks with SageMaker for model development, fine-tuning, and deployment. • Experience with distributed training (multi-GPU or multi-node) and performance optimization for inference. • Strong data-engineering skills on AWS: Amazon S3, AWS Glue, Lake Formation, Redshift for AI/ML data pipelines. • Experience building end-to-end AI/ML workflows using services like AWS Lambda, Step Functions, API Gateway, and containerized deployments on Amazon EKS / AWS Fargate. • Hands-on experience with CI/CD for AI/ML using AWS CodePipeline, CodeBuild, SageMaker Pipelines, or similar. • Proficiency in monitoring and operating AI systems using Amazon CloudWatch and SageMaker Model Monitor. • Strong understanding of AI governance, security, and compliance on AWS, including IAM, KMS, and data privacy patterns. • Familiarity with AI ethics and bias detection/mitigation (e.g., using SageMaker Clarify or similar tools). • Working knowledge of Google Cloud AI tools (e.g., Vertex AI, Cloud AutoML, BigQuery ML) sufficient to reason about multi-cloud architectures and integration points. • Proven ability to mentor peers, run enablement sessions, and collaborate across Sales, CS, and Product.

🏖️ Benefits

• Unlimited Vacation • Flexible Working Options • Health Insurance • Parental Leave • Employee Stock Option Plan • Home Office Allowance • Professional Development Stipend • Peer Recognition Program