AI Solution Engineer - Manager

Job summary

The AI Solution Engineer acts as a bridge between industry architects and development teams to shape and deliver feasible AI solutions. They support the sales process by demonstrating technical excellence and communicating the business value of AI prototypes to clients.

Job details

About the role We are looking for an experienced AI Solution Engineer to act as the link between PwC’s industry architects, who identify AI business cases, and the firm’s development capabilities. This role shapes AI solutions, meets client needs, and delivers measurable business value and technically feasible solutions. The AI Solution Engineer is a key technical resource responsible for selecting, designing, demonstrating, and delivering prototype solutions that align with customer needs and business goals during early engagement. As a trusted advisor, the Solution Engineer has a strong mix of technical expertise, problem-solving skills, and business acumen to effectively create cloud prototypes to demonstrate and communicate the value of solutions to both technical and non-technical stakeholders. They provide experience in identifying viable and feasible AI solutions to address specific client issues and demonstrate PwC’s technical capability as part of proposals. They demonstrate extensive knowledge of hyperscaler AI offerings, understanding all of the technical requirements and dependencies of a product/solution and explaining them to potential clients What your days will look like; Primarily sales-oriented, this role is focused on supporting the sales process by bridging the gap between technical teams and non-technical salespeople. The role helps sales teams select and prospects understand the AI/ML solution, demonstrates how it solves their business problems, and assists in demonstrating AI technical excellence to the client in the early sales process This role is for you if you have: Extensive experience working with sales teams and shaping viable and feasible software solutions as part of process change for enterprise customers AI Model Architecture – Evidenced expertise in LLMs, SLMs, (Large Language Models/Small Language Models) performance, suitability, training requirements, and deployment Cloud & Hyperscalers – Practical experience with at least two of the following is required: AWS Bedrock/Sagemaker, Google Vertex AI, OpenAI and Azure ML is required An understanding of underlying statistics, machine learning and data science, data engineering and big data concepts is required An understanding of the process and data complexities and prerequisites, and success criteria needed to deliver a solution that meets user and business needs Cloud Security & FinOps – Knowledge of landing zones, security, and AI cost optimisation ​ What you’ll receive from us: No matter where you may be in your career or personal life, our benefits are designed to add value and support, recognising and rewarding you fairly for your contributions. We offer a range of benefits including empowered flexibility and a working week split between office, home and client site; private medical cover and 24/7 access to a qualified virtual GP; six volunteering days a year and much more.

What you’ll do

The AI Solution Engineer acts as a bridge between industry architects and development teams to shape and deliver feasible AI solutions. They support the sales process by demonstrating technical excellence and communicating the business value of AI prototypes to clients.

Requirements

Candidates must have extensive experience in shaping software solutions for enterprise customers and deep expertise in AI model architecture. Practical experience with cloud hyperscalers and a strong understanding of data science and security concepts are required.

Benefits

• Empowered flexibility
• Private medical cover
• 24/7 access to a qualified virtual GP
• Six volunteering days a year

Listed skills

• Machine learning · Preferred
• Stakeholder Management · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• AI Solution Engineering
• LLMs
• SLMs
• AWS Bedrock
• Sagemaker
• Google Vertex AI
• Azure ML
• Machine Learning
• Data Science
• Data Engineering
• Big Data
• Cloud Security
• FinOps
• Sales Support
• Technical Architecture
• Stakeholder Management
• Problem Solving
• Business Problems
• Business Acumen
• Artificial Intelligence
• Business Valuation
• Sales
• Technical Requirements
• Sales Process
• Sales Prospecting
• Software Solutions
• Statistics
• Cost Management
• Large Language Modeling
• Azure Machine Learning
• Gemini Enterprise Agent Platform
• Cloud Financial Management (FinOps)
• AWS SageMaker
• Model Architecture
• Small Language Model
• OpenAI

Job areas

• Technology
• Consulting
• Sales
• Data & Analytics
• Software
• Solutions Engineer
• Software Development / Engineering Manager
• Software Developers

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