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.

Hybrid

Structure: global Forward Deployment Engineering team

doitintl is hiring a Senior Cloud Architect, Field Engineering (GenAI Focus)