
Senior Cloud Architect, Delivery – GenAI
Posted Jul 15

Posted Jul 15
This is a fully remote position, open to applicants in Portugal.
• Spearhead the design and execution of production-grade ML and Generative AI solutions on AWS, while considering 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 complex business challenges into cloud architectures that are secure, reliable, cost-effective, and observable.
• Contribute to the evolution of how DoiT leverages AI/ML internally and for clients by transforming one-off solutions into reusable patterns and “gravel roads” that shape the product roadmap.
• Emphasize the health of the install base, product adoption, proactive engagements, and collaboration with account teams.
• Be the reliable cloud engineer that customers depend on for impactful technical optimization across cost, reliability, security, and performance.
• Design and assist in implementing solutions that enhance cost efficiency (rightsizing, reservations/commitments, storage optimization), boost reliability and resilience (HA/DR architectures, SLO/SLA-aware designs), fortify security posture (IAM, network segmentation, data protection, least-privilege), and minimize operational toil (automation, self-service, guardrails, policy enforcement).
• Plan and execute structured engagements such as Cloud Optimization Sessions, workshops on cost/efficiency/performance, security posture or reliability reviews, and architecture deep dives or 'well-architected' assessments.
• Address Expert Inquiry and support requests that necessitate deep cloud engineering expertise.
• Over 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, selecting the right services and patterns to achieve business and technical objectives.
• Advanced proficiency with AWS services pertinent to AI/ML and Generative AI.
• Practical experience with Amazon Bedrock for deploying and scaling foundational models and Generative AI workloads.
• Experience 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 rigorous 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.
• Comprehensive knowledge 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 with distributed training (multi-GPU or multi-node) and performance optimization for inference.
• Strong data engineering capabilities 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 using services like AWS Lambda, Step Functions, API Gateway, and containerized deployments on Amazon EKS/AWS Fargate.
• Practical experience with CI/CD for AI/ML utilizing AWS CodePipeline, CodeBuild, SageMaker Pipelines, or similar.
• 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 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 understand multi-cloud architectures and integration points.
• Established ability to mentor peers, conduct enablement sessions, and collaborate across Sales, Customer Support, and Product teams.
• Excellent communication skills across technical and business audiences; capable of simplifying complex concepts and influencing decisions.
• Natural ownership mentality: you escalate issues early, resolve them swiftly, and take responsibility for outcomes.
• Proven ability to work effectively in a remote-first, global environment.
• Unlimited Vacation
• Flexible Working Options
• Health Insurance
• Parental Leave
• Employee Stock Option Plan
• Home Office Allowance
• Professional Development Stipend
• Peer Recognition Program
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