Senior Cloud Architect, Delivery – GenAI

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

📋 Description

• Oversee the design and execution of production-quality ML and Generative AI solutions on AWS, considering multi-cloud scenarios.

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

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

• Contribute to DoiT’s internal and customer-facing AI/ML initiatives by transforming one-off solutions into reusable patterns and 'gravel roads' that shape the product roadmap.

• Prioritize the health of the install base, enhance product adoption, encourage proactive engagements, and collaborate with account teams.

⛳️ Requirements

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

• Demonstrable 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 GenAI.

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

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

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

• Knowledge of agentic capabilities and design patterns for AI agents that perform tasks autonomously and integrate with existing systems.

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

• Comprehensive understanding of Amazon SageMaker components such as Pipelines, Model Monitor, Data Wrangler, and SageMaker Clarify for bias detection and interpretability.

• Ability to integrate 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 optimizing performance for inference.

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

• Proven experience in building 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 grasp of AI governance, security, and compliance on AWS, including IAM, KMS, and data privacy practices.

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

• Working knowledge of Google Cloud AI tools (e.g., Vertex AI, Cloud AutoML, BigQuery ML) to reason about 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 with both technical and business audiences; able to simplify complex concepts and sway decisions.

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

• Proven ability to thrive 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