[Remote] Senior Cloud Architect, Field Engineering (GenAI Focus)

Note: The job is a remote job and is open to candidates in USA. DoiT is a global technology company that helps organizations leverage public cloud for business growth and innovation. They are seeking a Senior Cloud Architect to focus on GenAI advisory and implementation within their AWS-focused AI Field Engineering team, delivering high-impact AI engagements and driving customer success.ResponsibilitiesDeliver high-impact AI engagementsLead hands-on delivery for GenAI implementation engagements, funded implementation projects, technical proof-of-value engagements, and other customer-facing AI initiativesTranslate customer goals into practical architectures, implementation plans, and measurable technical outcomesBuild, configure, and validate AWS-native AI and data solutions, with emphasis on production-ready architectures and servicesOwn technical execution from discovery through delivery, including design reviews, workshops, implementation support, and executive-ready readoutsStep into complex customer situations where technical depth, speed, and credibility are requiredSupport product adoption by helping customers implement and integrate DoiT products as part of AI engagements and broader cloud initiativesContribute to new logo acquisition by using technical consulting, implementation engagements, and proof-of-value work to help open and progress new opportunitiesExpand the install base by helping existing customers adopt advanced features, launch new workloads, and move to higher-value product and service motionsStrengthen partner leadership by collaborating with AWS partner teams, supporting funded programs, and helping DoiT show up as a strategic technical partner in AI-related motionsIdentify patterns, reusable assets, and “gravel road” solutions that should become standard delivery approaches, playbooks, or product feedbackHelp move successful one-off customer work into repeatable solution packages, templates, and standardized offerings for the broader teamContribute to standardization of engagement sizing, delivery approach, and technical assets to improve team efficiency over timePartner closely with Solution Engineers, Account Managers, Customer Success Managers, Engagement Managers, and partner teams to scope and execute the right work at the right timeProvide technical leadership during discovery, planning, handoff, and deliveryHelp ensure customer engagements are well-scoped, well-documented, and tied to clear success criteriaMaintain clear visibility into active work, risks, dependencies, and next stepsUse the team’s operating systems and workflows to keep customer engagement data current and measurableContribute to adoption playbooks, funding workflows, Jira hygiene, and the management cadence needed to scale the Field Engineering modelSkillsExperience in customer-facing cloud architecture, technical consulting, solutions delivery, or field engineeringHands-on experience with AWS in real customer environmentsWorking knowledge of modern AI and GenAI architectures on AWS — particularly Amazon Bedrock (Knowledge Bases, model evaluation, guardrails), retrieval-augmented generation (RAG) patterns with vector databases, and agentic AI design patterns. Familiarity with AWS CDK or similar infrastructure-as-code for deploying AI workloadsAbility to move between technical depth and customer-facing communication with easeExperience leading workshops, discovery sessions, implementation activities, or technical POVsStrong judgment in ambiguous environments; able to simplify, prioritize, and move work forward without heavy process overheadComfortable working across sales, delivery, customer success, product, and partner stakeholdersNatural ownership mentality: escalate early, resolve fast, and own the outcomeExperience delivering GenAI workshops, technical assessments, or customer implementation engagementsExperience with the AWS Migration Acceleration Program (MAP), partner-funded implementation programs, or similar structured cloud adoption programsExperience building reusable technical assets, templates, or playbooks that improved delivery leverageExperience with Amazon SageMaker for MLOps workflows, model monitoring, or custom model deploymentFamiliarity with agentic AI frameworks (e.g., AgentCore, Strands, or similar orchestration tools)Hands-on experience with vector databases (Aurora pgvector, OpenSearch) in production RAG architecturesAWS cloud certificationsExperience with DoiT products, cloud cost optimization, Kubernetes, data engineering, or platform modernizationBenefitsUnlimited VacationFlexible Working OptionsHealth InsuranceParental LeaveEmployee Stock Option PlanHome Office AllowanceProfessional Development StipendPeer Recognition ProgramCompany OverviewDoiT Cloud Intelligence intent-aware FinOps platform goes beyond cost optimization to drive reliability, performance, and security. It was founded in 2011, and is headquartered in Santa Clara, California, USA, with a workforce of 501-1000 employees. Its website is https://www.doit.com.Company H1B SponsorshipDoiT has a track record of offering H1B sponsorships, with 3 in 2025, 2 in 2024, 4 in 2022. Please note that this does not guarantee sponsorship for this specific role.