Senior Cloud Architect, Delivery – GenAI

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

📋 Description

• Oversee the design and execution of production-quality ML and Generative AI solutions on AWS, with a focus on multi-cloud environments.

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

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

• Contribute to the evolution of how DoiT employs AI/ML both internally and with clients 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 engagement, and collaboration with account teams.

⛳️ Requirements

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

• A strong record of designing and operating large, distributed systems on AWS, selecting the right services and patterns to achieve business and technical objectives.

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

• Practical experience with Amazon Bedrock for deploying and scaling foundational models and Generative AI workloads.

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

• Excellent prompt engineering capabilities and knowledge of thorough model evaluation (quality, safety, performance).

• Comprehension of agentic capabilities and patterns for AI agents that can autonomously complete tasks and integrate with existing systems.

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

• Comprehensive understanding of Amazon SageMaker components, such as 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 optimizing performance 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.

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

• Proficient 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 frameworks.

• Knowledge of AI ethics and bias detection/mitigation techniques (e.g., utilizing SageMaker Clarify or similar tools).

• Familiarity with Google Cloud AI tools (e.g., Vertex AI, Cloud AutoML, BigQuery ML) sufficient to navigate multi-cloud architectures and integration points.

• Proven ability to mentor colleagues, conduct enablement sessions, and collaborate across Sales, CS, and Product teams.

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

• A natural ownership mindset: you escalate issues early, resolve them quickly, and take responsibility for the outcomes.

• Demonstrated capability to work effectively in a remote-first, global work environment.

🏝️ Benefits

• Unlimited Vacation

• Flexible Working Options

• Health Insurance

• Parental Leave

• Employee Stock Option Plan

• Home Office Allowance

• Professional Development Stipend

• Peer Recognition Program