Program 04Arvanord Academy · Advanced / Professional

AI Systems Engineer

The complete journey from business problem to operating system.

Coming SoonLearning time: Flagship program — full journey
Program price
$495

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  • Certificate of Completion
  • Self-paced, online
  • Professional technology education
About the program

The AI Systems Engineer program is the complete professional path: how a business problem becomes a workflow analysis, an opportunity calculation, a system architecture — and then a deployed, monitored, iterating production system.

It is built on the same method Arvanord uses in client engagements, from models and knowledge through to agents, integrations, evaluation, deployment and iteration.

The final project is a full AI system design for a real or simulated business process, reviewed against the standards used on commercial engagements.

What you will be able to do
  • Run a complete systems engineering process end to end
  • Architect models, knowledge, data, agents and integrations
  • Design approvals, permissions and evaluation frameworks
  • Plan deployment, monitoring and iteration
  • Produce professional-grade system architecture documentation
Audience
Senior technical professionalsArchitectsTechnical leadsConsultants building AI practices
Instructor

Arvanord engineering team — the engineers who architect and run client systems.

Prerequisites
  • Foundations-level understanding of AI systems
  • Professional experience in delivery, engineering or operations
Assessment

Final project — design a full AI system around a real or simulated business process.

Certificate

AI Systems Engineer — Certificate of Completion

Credential ID format: ARV-E-YYYY-NNNN

Curriculum

Program outline.

Module structure is published openly. Lesson content is produced to Arvanord's engineering documentation standard.

01From problem to system
  • Business problem framing
  • Workflow analysis
  • Opportunity calculation
  • System boundaries
02Architecture
  • System architecture
  • Model selection and strategy
  • Knowledge and data architecture
  • Agents and orchestration
03Integration
  • APIs and integrations
  • Interfaces and copilots
  • Human approval design
  • Security boundaries
04Assurance
  • Evaluation frameworks
  • Guardrails and reliability
  • Documentation standards
  • Governance
05Lifecycle
  • Deployment
  • Monitoring
  • Iteration and evolution
  • Operating model
06Final project
  • Design a full AI system
  • For a real or simulated business process
  • Architecture review
  • Certificate issuance
Beyond the course

Become an AI Systems Engineer

Academy programs teach systems thinking. Our engineering team builds the systems themselves.