PwCPosted 1w ago

Solution Engineering & AI Prototyping Specialist

Solution Engineering & AI Prototyping Specialist at PwC scores 67 out of 100 on AI centrality, which makes it AI Level 3 of 4 (Works on AI) on this board. The level measures how much of the work is AI, not seniority.

BucharestFull time

AI in this role

openaiazure-openai

ai-safety

Job Description & Summary

The opportunity

Accelerate pursuits and advisory engagements through compelling demonstrations, rapid prototypes and hands-on technical validation across Azure, data, AI and automation.

What you will be doing

Prototyping & demonstrations

Rapidly convert priority business use cases into demonstrations, proof-of-concept solutions and technical spikes.
Build clear, client-ready experiences that show workflows, data flows, controls and expected user interactions.
Prepare demo environments, scripts and supporting materials for workshops, proposals and executive presentations.
Capture reusable components, patterns and lessons learned.

Technical validation

Validate APIs, data access, integration patterns, model behavior, deployment options and non-functional requirements.
Estimate prototype effort and identify technical risks, constraints and prerequisites before larger mobilization.
Apply secure engineering practices, appropriate data handling and Responsible AI controls in prototype work.
Collaborate with the Cloud Architect on architecture decisions and with the Data & AI Manager on use-case intent and evaluation.

Advisory support & capability building

Contribute practical technical input to assessments, roadmaps, proposals and delivery plans.
Coach consultants on Microsoft demonstrations and support internal enablement sessions.
Maintain awareness of relevant Microsoft platform developments and assess their applicability to client needs.

What we need from you

4+ years in cloud engineering, software development, data engineering, AI engineering or solution engineering.
Hands-on experience with Azure services, APIs, identity, DevOps, data pipelines and modern application patterns.
Practical capability in Python or another modern language and experience building client-facing prototypes.
Strong communication skills and the ability to explain technical behavior to non-technical audiences.
Comfort working in ambiguous, time-sensitive pursuit and discovery settings.

Preferred qualifications

AI-102, AZ-204, DP-600, DP-203 or PL-600 certifications are desirable.
Experience with Azure OpenAI, Microsoft Fabric, Power Platform, GitHub or Azure DevOps is advantageous.
Professional-services or pre-sales experience is preferred.

Measures of success

Speed and quality of prototypes and demonstrations
Accuracy of technical validation and risk identification
Reuse of accelerators and technical assets
Contribution to proposals, workshops and qualified opportunities
Adherence to security, data-handling and Responsible AI expectations

Key interfaces

Microsoft Cloud Architect and the other core team members
PwC Advisory sector and functional leaders
Cybersecurity, risk, privacy, legal, tax, deals, change and delivery specialists
Microsoft alliance and partner ecosystem stakeholders
Client executives, business owners, technology leaders and delivery teams

#LI-BS1 #LI-Hybrid

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

AI SafetyOpenAIAzure OpenAI

Questions you could be asked

How do you think about the risk of an AI system in this kind of role failing silently?
Walk me through how you've used OpenAI in your day-to-day work.
What are the limits of Azure OpenAI that you've run into, and how did you work around them?
Describe a typical day in a role like this one: which parts run through AI directly?
If you removed AI from this role, what would be left, and how do you decide what still needs a human?

Adapt your resume

List these exact terms on your resume: AI Safety, OpenAI, and Azure OpenAI. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.

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