DoiT

Cloud Technology

SeniorCloudArchitect,FieldEngineering(GenAIFocus)

United Kingdom; Netherlands; Sweden; Estonia; Poland; Romania; Portugal FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Senior Cloud Architect, Field Engineering (GenAI Focus) at DoiT. Skills: GenAI, AWS, Cloud Architecture, Field Engineering. Deliver high-impact AI engagements. Lead hands-on delivery for GenAI implementation engagements”

What You'll Achieve.

Drive business growth and innovation; Operate in a well-architected and scalable state; Solve complex multicloud problems; Drive efficiency; Move from exploration to production outcomes; Add focused AI delivery capacity; Reduce single-person dependency risk; Scale repeatable customer outcomes; Improve team efficiency; Help ensure customer engagements are well-scoped, well-documented, and tied to clear success criteria; Scale the Field Engineering model; Help Field Engineering scale AI delivery; Create measurable impact across the business; Increase delivery capacity for AI work; Convert more technical engagement into durable product adoption and retention; Improve technical influence on pipeline and closed-won outcomes; Create repeatable AI delivery patterns that scale across regions and partner motions; Meet growing customer demand for AI-focused technical delivery

Industry & Context.

Cloud Technology
Problems you'll solve

Solve complex multicloud problems; Simplify, prioritize, and move work forward without heavy process overhead; Resolve fast

What They're Looking For.

Must Have

Customer-facing cloud architecture, Technical consulting, Solutions delivery, Field engineering, Hands-on experience with AWS, Working knowledge of modern AI and GenAI architectures on AWS, Amazon Bedrock (Knowledge Bases, model evaluation, guardrails), Retrieval-augmented generation (RAG) patterns with vector databases, Agentic AI design patterns, AWS CDK or similar infrastructure-as-code, Ability to move between technical depth and customer-facing communication, Experience leading workshops, Discovery sessions, Implementation activities, Technical POVs, Judgment in ambiguous situations, Simplify, prioritize, and move work forward, Comfortable working across sales, delivery, customer success, product, and partner stakeholders, Natural ownership mentality

Nice to Have

Experience delivering GenAI workshops, Technical assessments, Customer implementation engagements, AWS Migration Acceleration Program (MAP), Partner-funded implementation programs, Building reusable technical assets, Templates, Playbooks, Amazon SageMaker for MLOps workflows, Model monitoring, Custom model deployment, Agentic AI frameworks (e.g., AgentCore, Strands, or similar orchestration tools), Hands-on experience with vector databases (Aurora pgvector, OpenSearch) in production RAG architectures, AWS cloud certifications, DoiT products, Cloud cost optimization, Kubernetes, Data engineering, Platform modernization

What You'll Do.

Deliver high-impact AI engagements

Lead hands-on delivery for GenAI implementation engagements

Translate customer goals into practical architectures

and validate AWS-native AI and data solutions

Own technical execution from discovery through delivery

Step into complex customer situations

Drive outcomes across the four FE growth pillars

Support product adoption

Contribute to new logo acquisition

Expand the install base

Strengthen partner leadership

Turn field work into repeatable plays

Help move successful one-off customer work into repeatable solution packages

Contribute to standardization of engagement sizing

Work cross-functionally to close and deliver

Partner closely with Solution Engineers

Provide technical leadership during discovery

Ensure customer engagements are well-scoped

Operate with discipline

Maintain clear visibility into active work

Use the team’s operating systems and workflows

How You'll Work.

Team & Collaboration

Collaborate with AWS partner teams; Partner closely with Solution Engineers; Account Managers; Customer Success Managers; Engagement Managers; Partner teams

Communication Scope

Customer-facing communication

Process & Methodology

Simplify, prioritize, and move work forward without heavy process overhead, Maintain clear visibility into active work, risks, dependencies, and next steps, Use the team’s operating systems and workflows to keep customer engagement data current and measurable, Contribute to adoption playbooks, funding workflows, Jira hygiene, and the management cadence

Full Job Description

Location Our Senior Cloud Architect, Field Engineering (GenAI Focus) will be an integral part of our global Forward Deployment Engineering team. This role is based remotely in the he UK, Ireland, Estonia, Sweden, the Netherlands, and Israel. The job is also open to contractors in Eastern Europe or Portugal. About DoiT DoiT is a global technology company that works with cloud-driven organizations to leverage public cloud to drive business growth and innovation. We combine data, technology, and human expertise to ensure our customers operate in a well-architected and scalable state—from planning to production. Delivering DoiT Cloud Intelligence, the only solution that integrates advanced technology with human intelligence, we help our customers solve complex multicloud problems and drive efficiency. With decades of multicloud experience, we have specializations in Kubernetes, GenAI, CloudOps, and more. An award-winning strategic partner of AWS, Google Cloud, and Microsoft Azure, we work alongside more than 4,000 customers worldwide. The Opportunity We are hiring a Senior Cloud Architect to strengthen our AWS-focused AI Field Engineering capability inside Customer Experience. This is a customer-facing, delivery-heavy role focused on GenAI advisory and implementation engagements, business value assessment engagements, AWS-funded adoption programs, and complex technical adoption projects that help customers move from exploration to production outcomes. This role is designed as a more clearly defined Field Engineering job within the existing organization, not as a separate standalone team. The goal is to add focused AI delivery capacity, reduce single-person dependency risk, and scale repeatable customer outcomes through better execution, enablement, and feedback into the wider Field Engineering motion. You will contribute directly to the four Field Engineering growth pillars: product adoption, partner leadership, new logo acquisition, and install base expansion. To suppo

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