Senior Cloud Architect, Field Engineering – GenAI Focus

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

📋 Description

• Execute high-impact AI projects.

• Spearhead hands-on delivery for GenAI implementation projects, funded initiatives, technical proof-of-value engagements, and various customer-oriented AI activities.

• Convert customer objectives into actionable architectures, implementation strategies, and quantifiable technical results.

• Construct, configure, and verify AWS-native AI and data solutions, focusing on production-ready architectures and services.

• Oversee technical execution from discovery to delivery, including design assessments, workshops, implementation assistance, and executive-ready presentations.

• Address complex customer scenarios requiring technical expertise, speed, and credibility.

• Propel outcomes across the four Field Engineering growth pillars.

• Facilitate product adoption by assisting customers in the implementation and integration of DoiT products within AI engagements and broader cloud strategies.

• Aid in acquiring new clients by leveraging technical consulting, implementation efforts, and proof-of-value initiatives to open and advance new opportunities.

• Broaden the install base by supporting existing customers in adopting advanced features, launching new workloads, and transitioning to higher-value product and service offerings.

• Enhance partner leadership through collaboration with AWS partner teams, supporting funded programs, and positioning DoiT as a strategic technical partner in AI-related initiatives.

• Transform fieldwork into repeatable processes.

• Recognize patterns, reusable assets, and "gravel road" solutions that should evolve into standard delivery methods, playbooks, or product feedback.

• Assist in converting successful one-off customer engagements into repeatable solution packages, templates, and standardized offerings for the wider team.

• Contribute to the standardization of engagement sizing, delivery methodologies, and technical assets to enhance team efficiency over time.

• Collaborate across functions to secure and deliver work.

• Work closely with Solution Engineers, Account Managers, Customer Success Managers, Engagement Managers, and partner teams to define and execute appropriate work at the right time.

• Provide technical leadership throughout discovery, planning, handover, and delivery phases.

• Ensure that customer engagements are well-defined, thoroughly documented, and aligned with clear success criteria.

• Maintain operational discipline.

• Ensure transparency regarding active work, risks, dependencies, and subsequent steps.

• Utilize the team's operating systems and workflows to keep customer engagement data updated and measurable.

• Contribute to playbooks for adoption, funding processes, Jira maintenance, and the management cadence necessary for scaling the Field Engineering model.

⛳️ Requirements

• Proven experience in customer-facing cloud architecture, technical consulting, solutions delivery, or field engineering.

• Practical experience with AWS in genuine customer environments.

• Familiarity with contemporary AI and GenAI architectures on AWS, particularly Amazon Bedrock (Knowledge Bases, model evaluation, guardrails), retrieval-augmented generation (RAG) patterns using vector databases, and agentic AI design frameworks.

• Ability to navigate seamlessly between technical depth and customer-facing communication.

• Experience facilitating workshops, discovery sessions, implementation tasks, or technical proof-of-values.

• Strong decision-making skills in uncertain environments; capable of simplifying, prioritizing, and advancing work without excessive process overhead.

• Comfortable collaborating across sales, delivery, customer success, product, and partner stakeholders.

• Natural ownership mentality: escalate issues promptly, resolve them quickly, and take responsibility for outcomes.

• Bonus Points: Experience in delivering GenAI workshops, technical assessments, or customer implementation initiatives.

• Familiarity with the AWS Migration Acceleration Program (MAP), partner-funded implementation initiatives, or similar structured cloud adoption programs.

• Experience in developing reusable technical assets, templates, or playbooks that enhanced delivery efficiency.

• Experience with Amazon SageMaker for MLOps workflows, model monitoring, or custom model deployment.

• Knowledge of agentic AI frameworks (e.g., AgentCore, Strands, or comparable orchestration tools).

• Hands-on experience with vector databases (Aurora pgvector, OpenSearch) in production RAG architectures.

• AWS cloud certifications.

• Experience with DoiT products, cloud cost optimization, Kubernetes, data engineering, or platform modernization.

🏝️ Benefits

• Unlimited Vacation

• Flexible Working Options

• Health Insurance

• Parental Leave

• Employee Stock Option Plan

• Home Office Allowance

• Professional Development Stipend

• Peer Recognition Program