AI Solutions Architect / Presales Engineer

What the job involves​

In a presales role, you help a customer decide whether a product will work in their environment. You work with an Account Executive, who manages the commercial relationship. Your work includes discovery conversations, a proposed architecture, and a proof-of-concept (PoC). Engineers and security reviewers need enough evidence to assess the proposal.

With a large language model (LLM), the proposal also needs to address answer quality and operating cost. Prepare to explain how you would test wrong or unsupported answers on the customer’s data, and estimate cost as usage grows.

Background: Glassdoor Community thread on SE vs. SA vs. Solutions Consultant naming.

A day in the life​

The percentages below illustrate a possible split; they are not a measured average. Work out the solution with the customer before building the demonstration. The balance of discovery, building, and internal work depends on the employer and engagement.

Discovery & design: 50%

Discovery calls, design sessions, and architecture reviews to understand the customer’s requirements before proposing a purchase.

Building PoCs and demos: 30%

Wiring up a proof-of-concept, sizing an architecture, and estimating token/inference cost for whatever gets proposed.

Internal & enablement: 20%

Proposal and RFP writing, reference-architecture content, and strategizing the next opportunity with the sales team.

Check how much of the role covers presales and how much continues into delivery. That scope affects which experience you need to demonstrate.

Experience and entry paths​

Experience requirements depend on the level and the technical scope. The examples collected for this guide include both experienced architecture roles and junior programs:

Three routes to consider:

Customer-facing technical work gives you relevant examples to discuss. Implementation consulting, technical account management, and cloud professional services can involve translating a customer’s needs into a technical plan. If you come from software engineering, I would also practice discovery conversations and explaining a proposal to a buyer.

Use the skills below to choose what to practice and demonstrate.

Skills to practice​

These six areas organize the preparation described in the postings.

Communication and discovery: ask questions that reveal the constraints behind a request. Budget, security requirements, and existing vendor commitments can change what you should propose.

Cloud and infrastructure: AWS, GCP, or Azure, with enough hands-on fluency to defend an architecture live, not just describe one from a slide. Enough Docker/Kubernetes literacy to stand up a containerized PoC without help.

AI and language models: retrieval-augmented generation (RAG), which provides source material to a model, and the trade-offs in storing and retrieving that material. Prepare prompt design, agents, and tool use. Explain the assumptions behind an estimate of model usage and inference cost.

Business judgment: estimate total cost of ownership (TCO) and return on investment (ROI). Understand procurement and requests for proposals (RFPs). Qualification frameworks such as MEDDIC or MEDDPICC help structure questions about whether an opportunity is ready to progress.

Demos and live presentation: build and run a PoC in front of an audience. Practice recovering if it breaks, and explain the architecture while answering questions.

Writing: proposals, RFP responses, and reference architectures. Blog posts and tutorials can also show prospects how you explain and solve a technical problem.

Match your preparation to the platform being sold. For cloud platforms, practice infrastructure and cost estimates. For platforms such as Salesforce or ServiceNow, practice configuration and mapping a business process. For AI vendors, practice retrieval and agent design. Check the posting before assuming any of these areas dominates the role.

The curriculum covers the AI application layer. Add the sales, cloud, and business-case practice listed below.

Curriculum mapping

What the curriculum covers​

Use your projects to practice explaining an architecture and its limits under questioning.

The interview​

Prepare to ask discovery questions, explain a design, and respond to objections. Coding requirements vary by vendor. Ask your recruiter which practical exercises and presentations are part of the process.

1. 1

   Recruiter screen

   Discuss your background and why you want a role that combines technical work with sales.

2. 2

   Live design / discovery round

   Given an unclear prompt, ask questions, propose an architecture, and explain your choices under questioning.

   What to expect, how to prepare, and what to have ready →

3. 3

   Case-study / PoC round

   A hypothetical customer hands you a vague ask, and you work it live from discovery through a proposed architecture and demo plan.

   Practice discovery, architecture, and a demo plan

   The framework, plus full end-to-end walkthroughs →

4. 4

   Behavioral / stakeholder round

   A mock customer call: objection handling, value anchoring, and navigating a deal team of Account Executive, delivery, and legal/procurement.

   Sample scenarios and how to work through them →

5. 5

   Exec / culture round (some companies)

   At larger vendors, a final round with a senior leader or cross-functional panel, weighted more on values fit than technical depth.

For a specific example, the Databricks Solutions Architect posting lists architecture interviews, live coding, and a build/demo/pitch exercise. Prepare for the format your employer uses rather than assuming presales means a presentation alone.

Before applying, check whether the title describes the presales work you want.

Presales vs. the adjacent titles

Is this really the role you want?​

Employers use these titles differently. Compare responsibilities and whether the work takes place before or after a contract is signed. The table is a starting point for reading a posting:

Check the posting and ask people in that role at the company what they own.

Finding openings​

Search the titles below, then compare the responsibilities with the table above. Check the expected balance of customer work, building, and delivery.

Places to check for openings:

Check whether a posting requires or recommends a certification. The research names AWS Certified Solutions Architect, AWS Certified AI Practitioner, Azure AI Engineer Associate, and Salesforce Agentforce Specialist as options tied to particular platforms. Choose the relevant platform, then check its current exam details before registering.

I would lead with a project you can demonstrate and a discovery conversation you can explain. Use certifications to support those examples and address requirements in the posting.

Compare base pay with the full package, including any commission or bonus.

Context, not a headline number

Compensation​

Check whether a posting gives base pay or on-target earnings (OTE), which includes the expected commission or bonus. Compare locations and levels, and use the employer’s current posting when discussing an offer.

Go deeper​

• Glassdoor Community: Sales Engineer vs. Solutions Engineer vs. Solutions Consultant vs. Solutions Architect
• ZipRecruiter: AI Solutions Architect salary
• Levels.fyi: Databricks Solution Architect compensation
• A day in the life of a Microsoft Pre-Sales Architect
• AWS Certified Solutions Architect – Associate exam guide
• Presales AI Solutions Architect posting (Solvd, via Dice)