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- Tasks: Shape AI solutions and bridge the gap between technical teams and sales.
- Company: Join PwC, a leader in innovative AI solutions with a collaborative culture.
- Benefits: Flexible working, private medical cover, and six volunteering days annually.
- Why this job: Make a real impact by delivering cutting-edge AI solutions to clients.
- Qualifications: Experience in AI model architecture and cloud technologies required.
- Other info: Dynamic role with opportunities for personal and professional growth.
The predicted salary is between 43200 - 72000 £ per year.
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.
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
- An understanding of underlying statistics, machine learning and data science, data engineering and big data concepts
- 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
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.
AI Solution Engineer - Manager in London employer: PwC UK
Contact Detail:
PwC UK Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Solution Engineer - Manager in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend relevant events, and engage with professionals on platforms like LinkedIn. We can’t stress enough how important it is to build relationships that could lead to job opportunities.
✨Tip Number 2
Showcase your skills! Create a portfolio or a GitHub repository where you can display your AI projects and prototypes. This gives potential employers a tangible way to see what you can do, and we all know actions speak louder than words!
✨Tip Number 3
Prepare for interviews by practising common questions and scenarios related to AI solutions. We recommend doing mock interviews with friends or mentors to boost your confidence and refine your responses.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we often have exclusive roles listed there that you won’t find anywhere else. Don’t miss out on your dream job!
We think you need these skills to ace AI Solution Engineer - Manager in London
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter to highlight your experience with AI solutions and cloud technologies. We want to see how your skills align with the role, so don’t hold back on showcasing your relevant projects!
Showcase Your Technical Skills: Don’t forget to mention your expertise in LLMs, SLMs, and any cloud platforms you’ve worked with. We’re looking for someone who can bridge the gap between technical and non-technical teams, so let us know how you’ve done that in the past.
Be Clear and Concise: When writing your application, keep it straightforward and to the point. We appreciate clarity, so make sure your achievements and experiences are easy to read and understand. Avoid jargon unless it’s necessary!
Apply Through Our Website: We encourage you to submit your application through our website. It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at PwC UK
✨Know Your AI Inside Out
Make sure you brush up on your knowledge of AI models, especially LLMs and SLMs. Be ready to discuss their performance, training requirements, and deployment strategies. This will show that you’re not just familiar with the concepts but can also apply them in real-world scenarios.
✨Bridge the Gap
Since this role involves liaising between technical teams and salespeople, practice explaining complex AI solutions in simple terms. Prepare examples of how you've successfully communicated technical details to non-technical stakeholders in the past.
✨Showcase Your Cloud Experience
Familiarise yourself with at least two cloud platforms like AWS, Google Cloud, or Azure. Be prepared to discuss specific projects where you’ve used these tools to deliver AI solutions, highlighting any challenges you faced and how you overcame them.
✨Understand Business Needs
Demonstrate your ability to align AI solutions with business goals. Think of examples where you identified client needs and shaped solutions accordingly. This will show that you have the business acumen needed for the role.
