Senior Cloud Architect, Delivery – GenAI

This is a fully remote position, open to applicants in Netherlands.

📋 Description

• Oversee the design and execution of production-level Machine Learning (ML) and Generative AI solutions on AWS, with consideration for multi-cloud environments.

• Serve as a hands-on expert and trusted advisor for clients managing AI/ML workloads at scale, guiding them from initial discovery to deployment and optimization.

• Convert intricate business challenges into secure, reliable, cost-effective, and observable cloud architectures.

• Enhance DoiT's utilization of AI/ML both internally and with clients by transforming one-off solutions into reusable patterns and “gravel roads” that shape the product roadmap.

• Emphasize the significance of install base health, product adoption, proactive engagements, and collaboration with account teams.

⛳️ Requirements

• At least 4 years of experience in architecting, deploying, and managing cloud-based AI/ML solutions, including production workloads.

• Proven experience in designing and operating large, distributed systems on AWS, effectively selecting services and patterns to fulfill business and technical objectives.

• Advanced expertise with AWS services pertinent to AI/ML and Generative AI.

• Practical experience with Amazon Bedrock for deploying and scaling foundation models and Generative AI applications.

• Background in fine-tuning and deploying Large Language Models (LLMs) and multimodal AI utilizing Amazon SageMaker (including JumpStart).

• Strong skills in prompt engineering and familiarity with comprehensive model evaluation (quality, safety, performance).

• Understanding of agentic capabilities and patterns for AI agents that autonomously execute tasks and integrate with existing systems.

• Experience with Amazon Q Business and Amazon Q Developer (or similar tools) to expedite insight generation and development workflows.

• In-depth knowledge of Amazon SageMaker components, including Pipelines, Model Monitor, Data Wrangler, and SageMaker Clarify for bias detection and interpretability.

• Proficiency in integrating TensorFlow, PyTorch, and other ML frameworks with SageMaker for model development, fine-tuning, and deployment.

• Experience in distributed training (multi-GPU or multi-node) and performance optimization for inference.

• Strong data-engineering capabilities on AWS: Amazon S3, AWS Glue, Lake Formation, and Redshift for AI/ML data pipelines.

• Experience in constructing end-to-end AI/ML workflows using services such as AWS Lambda, Step Functions, API Gateway, and containerized deployments on Amazon EKS / AWS Fargate.

• Hands-on experience with CI/CD for AI/ML utilizing AWS CodePipeline, CodeBuild, SageMaker Pipelines, or similar tools.

• Proficiency in monitoring and managing 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 strategies.

• Familiarity with AI ethics and bias detection/mitigation (e.g., utilizing 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 colleagues, conduct enablement sessions, and collaborate across Sales, Customer Success, and Product teams.

• Excellent communication skills across both technical and business audiences; capable of simplifying complex concepts and influencing decisions.

• Natural ownership attitude: you escalate issues early, resolve them quickly, and take responsibility for the outcomes.

• Demonstrated capability 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