Senior Cloud Architect, Delivery – GenAI

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

📋 Description

• Lead the design and execution of production-ready ML and Generative AI solutions on AWS, with consideration for multi-cloud settings.

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

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

• Contribute to the evolution of DoiT's internal use of AI/ML and client interactions by transforming one-off solutions into reusable frameworks and “gravel roads” that shape the product roadmap.

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

⛳️ Requirements

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

• Demonstrated success in designing and managing large, distributed systems on AWS, selecting suitable services and patterns to achieve business and technical objectives.

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

• Hands-on experience with Amazon Bedrock for the deployment and scaling of foundational models and Generative AI workloads.

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

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

• Understanding of autonomous AI agent capabilities and patterns for tasks that integrate with existing systems.

• Familiarity with Amazon Q Business and Amazon Q Developer (or similar tools) to enhance 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.

• Proficient in 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, including Amazon S3, AWS Glue, Lake Formation, and Redshift for AI/ML data pipelines.

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

• Practical experience with CI/CD for AI/ML using AWS CodePipeline, CodeBuild, SageMaker Pipelines, or similar tools.

• Proficient in monitoring and managing AI systems leveraging Amazon CloudWatch and SageMaker Model Monitor.

• Strong understanding of AI governance, security, and compliance on AWS, including IAM, KMS, and data privacy protocols.

• Familiarity with AI ethics and bias detection/mitigation, such as using SageMaker Clarify or comparable tools.

• Working knowledge of Google Cloud AI tools (e.g., Vertex AI, Cloud AutoML, BigQuery ML) sufficient to evaluate multi-cloud architectures and integration points.

• Proven capability to mentor colleagues, conduct enablement sessions, and collaborate across Sales, Customer Success, and Product teams.

• Exceptional communication skills for both technical and business audiences; able to simplify complex concepts and influence decision-making.

• Natural ownership mindset: you escalate issues promptly, resolve them swiftly, and take responsibility for outcomes.

• Demonstrated ability to work successfully 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