Becoming enabled in cloud AI Ethics, Compliance and Security sales/solutions engineering and being able to close the deals with the sales team is a highly paid and sought after skillset.   

For example, Security Sales engineers can make $134,200 per year "base" with variables (bonuses and commissions). 

For example: A security sales engineer may be offered an 80/20 or a 70/30 split when it comes to base/variable compensation.

• Base - $150,000
• Variable - $30,000

(Not to mention the non monetary benefits such as customer engagement at trade shows, lunch and learns and company engagement at company sales events.)

Learn about the critical value a highly skilled presales cloud solutions architect can bring to an organization and its customers.

(Beginner/Intermediate) This official CRAIEO certification course has been designed for anyone who wants to become a proven presales cloud solutions architect and leader.    

Demand for AI-aware presales and solutions architects has been exponentially growing year over year, and learning about cloud solutions architecture can really elevate your career opportunities in the world of cloud computing technology. 

A presales cloud solutions architect is a technical specialist who develops proposals, technical scope, and pricing models for innovative technical solutions for clients. This role generates revenue for the organization.

Presales solution architects are considered to be the clients' trusted advisors. They are responsible for the technical solutions proposed during the sales cycle. 

Did you know that, in October 2024, the average salary for a Solution Architect in the United States was $162,309 per year, according to Glassdoor?

Entry level solutions architect positions start at $93,026 per year while the most sought-after solutions architects can make over $250,000 per year.

As an AI-enabled solutions architect, you will be on the front lines to propose the right technical requirements to meet client goals and function as a liaison between your sales and engineering groups.

Once you complete this official Certified Responsible AI Ethics Officer (CRAIEO) certification course, you will be truly prepared to join your organization's highly sought-after solutions architecture experts.

Let us help you get enabled with presales engineering and architecture. So what are you waiting for? Let us get started!

Join this Digital Crest Institute (DCI) course now and elevate your career!

AI Aware Solutions Architects requires a wealth of various skill sets, which are covered on the exam.  

The certification exam will test candidates on the following exam objectives.

• AI/ML Fundamentals 
• Identifying and Qualifying Opportunities 
• Solution Development and Proposal 
• Closing and Relationship Management 

Certified Cloud AI Solutions Architect (CCASA)

Exam Objectives

Certified Cloud AI Solutions Architect (CCASA)

Exam Objectives

Domain 1: AI/ML Fundamentals (35%)

1.1 Core Concepts:

• Define AI, ML, and Deep Learning (DL) and their key differences.
• Explain common AI/ML use cases and applications across various industries.
• Describe different types of machine learning (supervised, unsupervised, reinforcement learning).
• Define and differentiate between Generative AI, Predictive AI, Agentic AI, and others.
• Define what algorithms are and the differentiation between them.
• Identify the major programming languages used in AI.
• Describe how AI works at a high level for a non-technical client.

1.2 AI/ML Value Proposition:

• Articulate the benefits of AI/ML solutions for businesses.
• Identify potential challenges and limitations of AI/ML adoption.
• Explain the importance of data in AI/ML solutions.
• Define the four pillars of AI Strategy
• Identify common data sources used in AI/ML deployment
• Describe the AI Project Lifecycle

1.3 AI/ML Landscape and Services:

• Identify key players in the AI/ML market (cloud providers, technology vendors, etc.).
• Recognize standard AI/ML tools, platforms, and frameworks.
• Stay updated on emerging trends and advancements in AI/ML.
• Identify potential clients and industries benefiting from AI/ML solutions.
• Describe everyday use cases for AI services in the Financial, Logistics, and Technology sectors.
• Describe the growth rate of AI Year over Year.

Domain 2:  Solution Development and Proposal (30%)

2.1 Solution Design:

• Design AI/ML solutions tailored to specific client needs and objectives.
• Select appropriate AI/ML techniques and technologies for the proposed solution.
• Define data requirements, model development, and deployment strategies.

2.2 Value Proposition and ROI:

• Clearly articulate the value proposition of the proposed AI/ML solution.
• Develop a compelling business case and demonstrate potential ROI.
• Address client concerns and objections regarding AI/ML adoption.
• Walk through why a Proof of Concept (POC) and define expectations.
• Perform a demonstration with a customer for AI services.
• Perform a whiteboard discussion with a customer for AI services.

2.3 Proposal Development and AI Cloud Fit:

• Describe what an RFP is and why they are commonly used in procurements.
• Create professional and persuasive proposals outlining the solution, timeline, and pricing.
• Effectively communicate value around technical details clearly and concisely.
• Describe what an AI Cloud Fit means and how to define based on client needs.

Domain 3:  Customer Relationship Management (35%)

3.1 Closing Techniques:

• Address client concerns and negotiate final terms.
• Manage the transition from sales to project implementation.
• Define what a stakeholder is and how they affect projects.
• Identify potential clients and industries benefiting from AI/ML solutions.
• Develop effective lead generation strategies for AI/ML services.

3.2  Building Long-Term Relationships:

• Define what a trusted advisor is and their traits.
• Identify common objections to AI projects and how to overcome them.
• Describe what a value proposition is and how to identify required metrics.
• Describe AI value-driven executive messaging.

3.3 Sales Cycle and Qualifying the Opportunities

• Describe how to conduct discovery for a potential AI project.
• Identify what the right questions are for identifying business outcomes
• Describe how to qualify the AI Opportunity
• Describe the process for performing a needs analysis
• Describe how to create that win-win situation in a potential AI deal.
• Understand what a Solution Selling Mindset is.

4.3  Ethical Considerations:

• Understand and address ethical considerations in selling AI/ML solutions.
• Promote responsible AI practices and ensure transparency with clients.
• Maintain client confidentiality and data privacy.

Successful Candidates will Receive a Digital Certification and a Digital Badge which can be posted and validated online.

A Free Study Guide is also provided online. 

Who should take this course and certification exam. 

• Anyone that is in a Pre-Sales Role or who may want to become a Pre-Sales professional.
• Anyone that has 1 year of cloud computing experience.
• Anyone that wants to prove they are competent in Presales and technical cloud solutions should consider obtaining the CCPSA certification.
• Anyone who wants to learn more about cloud computing architecture, solutioning and cost management.

Vendor Agnostic means that the exam is not tied to the specific products and services of a vendor.

We do cover in the course content specific examples but the test will not solely rely on testing on AWS, GCP, etc. 

The certification itself costs $199.00 USD which includes one free retake if needed.

The Full course and exam package bundle is available for $299.00

Continuing Education is a critical component to ensure that successful candidates maintain their certifications and keep up with changing times around technology.

The CEU requirements will be made available in March 2024 and will require 50 hours of continuing education units (CEU) over 3 years.  Fee will be $50.00.

Yes, both free and paid practice questions will be available on Digital Crest Institute (DCI) and Udemy.

The Certified Responsible AI Ethics Officer (CRAIEO) certification is valid for three years without Continuing Education. 

The credential will expire unless CE Credits are submitted.  

CE Credit information will be provided 6 months prior to expiration.

Exam is taking online and is not proctored. 

The CCASA exam is 75 Questions and is timed at 90 Minutes. 

Questions are multiple choice.

Allowance of 15 Minutes is given for nonnative English speakers if requested.

Coaching is available for the Certified Responsible AI Ethics Officer (CRAIEO) exam and is discounted on an hourly basis for this exam. 

Contact Us for more information.

Base rates would be $99.00 per hour.

The Certified Responsible AI Ethics Officer (CRAIEO) official exam preparation course (4 hours of content) is available on Digital Crest Institute.