Ai & Automation Engineer
A production focused programme for technical teams building and operating AI driven automation.
You will design and deploy low code workflows, integrate enterprise systems via APIs and connectors, configure and control agents, and embed security, governance, logging and human oversight from the outset.
The curriculum builds engineering depth across workflow reliability, error handling, testing, controlled release and performance monitoring, alongside business analysis and value measurement.
The result is production ready AI automation that is secure, scalable and engineered to deliver measurable operational impact.
- Design and deploy production ready AI automation across enterprise workflows
- Integrate core business systems using APIs, connectors and secure data patterns
- Configure and govern AI agents with clear guardrails and human oversight
- Engineer resilient workflows with error handling, retries and observability built in
- Test, release and support automation using disciplined production controls
- Measure performance, prove value and continuously
This programme equips you to move from experimentation to engineered, production grade AI automation that delivers measurable impact.
Enrol now and start building automation that performs reliably in real production environments.
.
Course Content
FULLY FUNDED
Core Technical Capabilities
What You Will Learn
Connectors and API calls
Iterative prompt engineering
Embedding GenAI in automations
Engineering reliable workflows with triggers, actions, advanced logic, error handling, retries and idempotency
Configuring and running agents with guardrails and orchestration patterns
Governance and Production Controls
What You Will Learn
Test, documentation and controlled release practices
Logging and telemetry
Risk mitigation strategies
Algorithmic impact assessment
Privacy, security and ethical controls
Business Analysis and Process Improvement
What You Will Learn
Business process modelling
Stakeholder management
Lean Six Sigma techniques
Identification of waste
Value stream mapping
Continuous improvement
Delivery and Value Measurement
What You Will Learn
Risk, issues and dependency management
Benefits realisation and value reporting
Outcome evaluation against goals
Data analysis
Measuring before and after impact
Practical Application Areas
Typical automation projects include:
Knowledge assistants
Ticket and case triage
Agent assist
Reporting automation
Predictive analytics triggers
Risk detection
Approval workflows
End to end automation across systems
This programme builds the technical depth, governance discipline and production confidence required to design, deploy and operate AI automation in real environments.
Join the programme and start delivering AI solutions that work reliably, scale securely and prove their value.