Senior Cloud Architect, Delivery – GenAI

🕒 Junho 30

🌐 Portugal, Reino Unido, +5 outros países – Remoto

🇵🇹 Portugal – Remoto 🇬🇧 Reino Unido – Remoto (RU) 🇮🇪 Irlanda – Remoto 🇪🇪 Estônia – Remoto 🇸🇪 Suécia – Remoto 🇳🇱 Holanda – Remoto 🇮🇱 Israel – Remoto

⏰ Tempo Integral

🟠 Sênior

☁️ Engenheiro de Cloud

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DoiT International

SiteLinkedInTodas as Vagas

201 - 500 funcionários

Fundada em 2014

☁️ SaaS

💼 Consultoria

SaaS • Cloud Services • Consulting

DoiT International é uma empresa de serviços em nuvem que oferece soluções completas para gerenciar e otimizar a infraestrutura em nuvem em múltiplas plataformas, como AWS, Google Cloud e Microsoft Azure. Seus serviços incluem gestão de custos em nuvem, inteligência de cargas de trabalho, automação e consultoria. A DoiT International ajuda as empresas a otimizar seus ambientes de nuvem, melhorar o desempenho e fortalecer a segurança por meio da combinação de tecnologia avançada e consultoria especializada.

Descrição

• Lead the design and implementation of production-grade ML and Generative AI solutions on AWS (with awareness of multi-cloud environments). • Act as a hands-on expert and trusted advisor for customers running AI/ML workloads at scale, from initial discovery through deployment and optimization. • Translate complex business problems into cloud architectures that are secure, reliable, cost-efficient, and observable. • Help evolve how DoiT uses AI/ML internally and with customers by turning one-off solutions into reusable patterns and “gravel roads” that influence the product roadmap. • Focus more on install base health, product adoption, proactive engagements, and account-team work. • Be the trusted cloud engineer customers lean on for high-impact technical optimization work across cost, reliability, security, and performance. • Design and help implement solutions that improve cost efficiency (rightsizing, reservations/commitments, storage optimization, etc.), increase reliability and resilience (HA/DR architectures, SLO/SLA‑aware designs), strengthen security posture (IAM, network segmentation, data protection, least‑privilege), and reduce operational toil (automation, self‑service, guardrails, policy enforcement). • Plan and deliver structured engagements such as Cloud Optimization Sessions, cost/efficiency/performance workshops, security posture or reliability reviews, and architecture deep dives / 'well‑architected' style assessments. • Respond to Expert Inquiry / support requests that require deep cloud engineering expertise.

🎯 Requisitos

• 4+ years of experience architecting, deploying, and managing cloud-based AI/ML solutions, including production workloads. • Proven track record designing and operating large, distributed systems on AWS, selecting appropriate services and patterns to meet business and technical goals. • Advanced proficiency with AWS services relevant to AI/ML and GenAI. • Hands-on experience with Amazon Bedrock for deploying and scaling foundation models and Generative AI workloads. • Experience fine-tuning and deploying Large Language Models (LLMs) and multimodal AI using Amazon SageMaker (including JumpStart). • Strong prompt engineering skills and familiarity with rigorous model evaluation (quality, safety, performance). • Understanding of agentic capabilities and patterns for AI agents that autonomously perform tasks and integrate with existing systems. • Experience with Amazon Q Business and Amazon Q Developer (or similar tools) to accelerate 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. • Proficiency 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: Amazon S3, AWS Glue, Lake Formation, Redshift for AI/ML data pipelines. • Experience 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 experience with CI/CD for AI/ML using AWS CodePipeline, CodeBuild, SageMaker Pipelines, or similar. • 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 to reason about multi-cloud architectures and integration points. • Proven ability to mentor peers, run enablement sessions, and collaborate across Sales, CS, and Product. • Excellent communication skills across technical and business audiences; able to simplify complex ideas and influence decisions. • Natural ownership mentality: you escalate early, resolve fast, and own the outcome. • Demonstrated ability to work effectively in a remote-first, global environment.

🏖️ Benefícios

• Unlimited Vacation • Flexible Working Options • Health Insurance • Parental Leave • Employee Stock Option Plan • Home Office Allowance • Professional Development Stipend • Peer Recognition Program