At a Glance
- Tasks: Lead innovative Data & AI solutions for enterprise clients and mentor delivery teams.
- Company: Join a top Microsoft Global Alliance Partner with a vibrant culture.
- Benefits: Extensive training, real-time access to resources, and collaboration with industry experts.
- Other info: Dynamic role with continuous learning and career growth opportunities.
- Why this job: Shape the future of Data & AI while making a real impact on client success.
- Qualifications: Experience in GenAI, data platforms, and strong architectural skills required.
The predicted salary is between 70000 - 90000 £ per year.
We’re hiring a senior, client‑facing Solution Architect to help enterprise clients bring their vision to life through impactful, responsible, and scalable Data & AI solutions. The role involves shaping deals, crafting solution roadmaps, mentoring delivery teams, and leading Agentic AI and data platform engagements.
Key Responsibilities
- Work closely with delivery teams and client stakeholders to provide technical leadership, shape deals and propositions, drive architectural decisions, create plans and roadmaps, and produce design artifacts.
- Play a key role in the sales process by creating innovative solutions, shaping high‑level design, estimating, and defining contractual details for client proposals in collaboration with subject matter experts.
- Coaching and mentoring junior colleagues within the team and across the organization.
- Translate complex technical concepts into easy‑to‑understand language and value‑based outcomes for senior business stakeholders, technology leaders, and internal sales teams.
- Engage early with clients, partners, and sales teams to support origination, deal qualification, requirements capture, and solutioning; recommend best practices and approaches to achieve optimal outcomes; and represent the solution in deal reviews and client presentations.
- Collaborate with Data & AI leadership to shape current and future offerings, accelerators, and background IP to support GTM activities.
- Drive the evolution of best practices and methodologies for AI development, including data management, model training, fine‑tuning, and deployment.
- Stay abreast of the latest advancements in AI and data technologies and incorporate relevant innovations into solutions.
Qualifications
- Excellent working knowledge of GenAI/Agentic AI, Microsoft Fabric, and/or Databricks.
- Awareness of channels to market and the ability to work within a Microsoft and partner ecosystem to ensure customer success.
- High energy and intent to help clients understand the fast‑moving Data & AI industry and product/service evolution.
- Experience creating technical visions, high‑level architectures, and delivery roadmaps for large programs involving the latest data platform concepts, including scaling AI across enterprises.
- Capability to produce design artifacts and present them for approval at architectural forums attended by multidisciplinary stakeholders, from engineering to senior (C‑level) client executives.
- In‑depth understanding of modern Data & AI capabilities such as structured/unstructured data analysis, streaming data, IoT, AI, GenAI, and related analytics fields.
- Experience designing and delivering large‑scale Data Platform solutions using approaches such as Lakehouse, Data Mesh, Fabric, and Cloud‑scale Analytics, focusing on performance, security, and reliability.
- Comfortable leading sales and business development opportunities with clients.
Benefits
- Opportunity to work for Microsoft’s Global Alliance Partner of the Year (14 years in a row) with extensive development and training (minimum 80 hours per year for training and paid certifications).
- Real‑time access to technical and skilled resources globally.
- Collaboration with some of the brightest Microsoft minds.
- Continuous learning, problem‑solving, and professional development opportunities.
Data & AI Architect in London employer: Dormont Manufacturing Co
As a leading player in the Data & AI sector, we pride ourselves on fostering a dynamic work culture that prioritises innovation and collaboration. Our employees benefit from extensive training opportunities, including a minimum of 80 hours per year dedicated to professional development, and the chance to work alongside some of the brightest minds in the industry. Located in a vibrant tech hub, we offer a unique environment where your contributions directly impact enterprise clients, making this an ideal place for those seeking meaningful and rewarding employment.
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We think this is how you could land Data & AI Architect in London
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We think you need these skills to ace Data & AI Architect in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Craft a Tailored Cover Letter:For a full-time role at Dormont Manufacturing Co, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Dormont Manufacturing Co. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Dormont Manufacturing Co
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
