[Remote] Copy of Senior Cloud Architect, Field Engineering (GenAI Focus) - Armenia

Note: The job is a remote job and is open to candidates in USA. DoiT is a global technology company that works with cloud-driven organizations to leverage public cloud to drive business growth and innovation. They are seeking a Senior Cloud Architect to strengthen their AWS-focused AI Field Engineering capability, with responsibilities including delivering high-impact AI engagements and driving outcomes across key growth pillars.

Responsibilities

• Deliver high-impact AI engagements
• Lead hands-on delivery for GenAI implementation engagements, funded implementation projects, technical proof-of-value engagements, and other customer-facing AI initiatives
• Translate customer goals into practical architectures, implementation plans, and measurable technical outcomes
• Build, configure, and validate AWS-native AI and data solutions, with emphasis on production-ready architectures and services
• Own technical execution from discovery through delivery, including design reviews, workshops, implementation support, and executive-ready readouts
• Step into complex customer situations where technical depth, speed, and credibility are required
• Drive outcomes across the four FE growth pillars
• Support product adoption by helping customers implement and integrate DoiT products as part of AI engagements and broader cloud initiatives
• Contribute to new logo acquisition by using technical consulting, implementation engagements, and proof-of-value work to help open and progress new opportunities
• Expand the install base by helping existing customers adopt advanced features, launch new workloads, and move to higher-value product and service motions
• Strengthen partner leadership by collaborating with AWS partner teams, supporting funded programs, and helping DoiT show up as a strategic technical partner in AI-related motions
• Turn field work into repeatable plays
• Identify patterns, reusable assets, and “gravel road” solutions that should become standard delivery approaches, playbooks, or product feedback
• Help move successful one-off customer work into repeatable solution packages, templates, and standardized offerings for the broader team
• Contribute to standardization of engagement sizing, delivery approach, and technical assets to improve team efficiency over time
• Work cross-functionally to close and deliver
• Partner closely with Solution Engineers, Account Managers, Customer Success Managers, Engagement Managers, and partner teams to scope and execute the right work at the right time
• Provide technical leadership during discovery, planning, handoff, and delivery
• Help ensure customer engagements are well-scoped, well-documented, and tied to clear success criteria
• Operate with discipline
• 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 needed to scale the Field Engineering model

Skills

• Experience in customer-facing cloud architecture, technical consulting, solutions delivery, or field engineering
• Hands-on experience with AWS in real customer environments
• Working 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 workloads
• Ability to move between technical depth and customer-facing communication with ease
• Experience leading workshops, discovery sessions, implementation activities, or technical POVs
• Strong judgment in ambiguous environments; able to simplify, prioritize, and move work forward without heavy process overhead
• Comfortable working across sales, delivery, customer success, product, and partner stakeholders
• Natural ownership mentality: escalate early, resolve fast, and own the outcome
• Experience delivering GenAI workshops, technical assessments, or customer implementation engagements
• Experience with the AWS Migration Acceleration Program (MAP), partner-funded implementation programs, or similar structured cloud adoption programs
• Experience building reusable technical assets, templates, or playbooks that improved delivery leverage
• Experience with Amazon SageMaker for MLOps workflows, model monitoring, or custom model deployment
• Familiarity with 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
• 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

Company Overview

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