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Symposium 06

Engineering & Build

Enterprise AI Engineering, Secure AI Development & AI System Build Lifecycle

This symposium focuses on one of the most operationally critical dimensions of enterprise AI transformation: How organizations actually engineer, develop, validate, secure, operationalize, and maintain AI systems in production environments.

Overview

Symposium Overview

This symposium focuses on one of the most operationally critical dimensions of enterprise AI transformation: How organizations actually engineer, develop, validate, secure, operationalize, and maintain AI systems in production environments.

Many organizations currently misunderstand AI implementation. They assume: Buying AI tools = AI transformation, Using copilots = AI engineering maturity, Prompting = AI system development.

In reality, enterprise AI engineering introduces entirely new disciplines across: AI application engineering, AI workflow engineering, Prompt engineering, Agent engineering, ML / LLM engineering, AI DevSecOps, AI validation & evaluation, AI operational governance, AI lifecycle integration.

This symposium helps organizations understand how enterprise AI systems are truly built, governed, validated, secured, deployed, and maintained at scale. It also addresses the transition from isolated experimentation → controlled enterprise AI engineering ecosystems.

Symposium Focus

This symposium focuses on one of the most operationally critical dimensions of enterprise AI transformation: How organizations actually engineer, develop, validate, secure, operationalize, and maintain AI systems in production environments.

Importance of the Domain
  • AI implementation chaos
  • Weak AI engineering governance
  • Insecure AI development
  • AI deployment instability
  • Poor AI testing practices
Expected Outcomes
  • How enterprise AI systems are truly engineered
  • Why AI engineering differs from traditional software development
  • How to secure AI development lifecycles
  • How to operationalize AI safely at scale
  • How to govern AI orchestration and automation
Target Audience

Who Should Attend

AI engineering teams
Software engineering departments
DevOps teams
DevSecOps teams
AI architects
Application development teams
Innovation teams
Platform engineering teams
Enterprise architects
Security engineering teams
Digital transformation teams
CIOs
CTOs
CISOs
Product engineering teams
Skills

Skills Participants Will Gain

Participants will gain the ability to:

Understand enterprise AI engineering lifecycle models
Understand AI application engineering principles
Understand enterprise prompt engineering practices
Understand AI agent engineering concepts
Understand AI DevSecOps integration
Understand secure AI development lifecycle principles
Understand AI validation and evaluation requirements
Understand AI deployment engineering concepts
Understand AI workflow orchestration models
Understand enterprise AI build governance
Understand AI operational engineering challenges
Understand scalable AI engineering architectures
Curriculum

What Will You Learn?

01Enterprise AI Engineering Fundamentals
02AI Application Engineering
03Prompt Engineering & Context Engineering
04ML, LLM & Agent Engineering
05DevSecOps for AI Systems
06AI Validation, Testing & Evaluation
07AI Workflow Orchestration & Automation
08Enterprise AI Deployment Engineering
09AI Operational Engineering & Lifecycle Management
10Future Enterprise AI Engineering Models
Enterprise Challenges

Enterprise Challenges Addressed

This symposium addresses challenges such as:

AI implementation chaos
Weak AI engineering governance
Insecure AI development
AI deployment instability
Poor AI testing practices
Uncontrolled AI automation
Weak orchestration governance
AI hallucination exposure
Operational AI failures
Fragmented AI engineering efforts
Lack of AI lifecycle visibility
Poor AI scaling practices
Executive Takeaways

Executive Takeaways

By the end of this symposium, leadership teams will understand:

How enterprise AI systems are truly engineered
Why AI engineering differs from traditional software development
How to secure AI development lifecycles
How to operationalize AI safely at scale
How to govern AI orchestration and automation
How to reduce AI operational instability
How to structure enterprise AI engineering ecosystems
Future Pathways

Suggested Future Pathways

CISAIP™
GAISP™
Secure AI Architecture Engineer (SAIAE)™
AiSOC-X™
AI Platform Engineering Programs
AI DevSecOps Programs
Agentic AI Engineering Tracks

Register Your Interest in this Symposium

Join the Engineering & Build symposium within the Executive AI Readiness Symposiums program.