Senior Cloud Architect, Delivery – GenAI

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

📋 Description

• Take the lead in designing and implementing production-grade ML and Generative AI solutions on AWS, with a consideration for multi-cloud environments.

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

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

• Contribute to the evolution of how DoiT leverages AI/ML internally and with 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.

⛳️ Requirements

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

• A proven history of designing and operating large, distributed systems on AWS, with the ability to select suitable services and patterns to achieve business and technical objectives.

• Advanced knowledge of AWS services relevant to AI/ML and GenAI.

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

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

• Strong skills in prompt engineering and an understanding of rigorous model evaluation practices (quality, safety, performance).

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

• Experience with Amazon Q Business and Amazon Q Developer (or similar tools) to enhance 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 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 using services like AWS Lambda, Step Functions, API Gateway, and containerized deployments on Amazon EKS / AWS Fargate.

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

• Proficiency in monitoring and operating 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 for reasoning about multi-cloud architectures and integration points.

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

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

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

• Demonstrated capability to perform 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