At a Glance
- Tasks: Lead teams to design AI-powered solutions and data-intensive platforms.
- Company: Join a leading financial tech firm focused on innovation.
- Benefits: Competitive salary, career growth, and opportunities for remote work.
- Other info: Dynamic role with a focus on cutting-edge technology and collaboration.
- Why this job: Be at the forefront of AI innovation in finance and make a real impact.
- Qualifications: Expertise in AI/ML and experience in regulated environments required.
The predicted salary is between 80000 - 100000 € per year.
As an AI Solution Architect, you will be the technical visionary leading cross-functional engineering teams to design and build data-intensive platforms and AI-powered solutions. You are responsible for the architectural integrity of the end-to-end data and AI lifecycle - specifically for Balance Sheet Management (BSM) - ensuring that models move seamlessly from ingestion and research into scalable, high-performance production environments.
Key Responsibilities
- System Blueprinting: Create robust technical blueprints for data pipelines and high-quality derived data products that align with AIPX architecture and performance standards.
- Technical Leadership: Provide strategic direction across cloud engineering, data architecture, and AI/ML capabilities to ensure solutions are secure, well-governed, and scalable.
- Engineering Excellence: Establish and enforce best practices for the automated SDLC, including DevOps/MLOps pipelines, coding standards, and rigorous testing frameworks.
- Stakeholder Synthesis: Translate complex business requirements from product owners and stakeholders into actionable, high-level technical plans and architectural roadmaps.
- AI Innovation: Drive the evaluation of emerging technologies, lead proofs of concept (PoCs), and embed responsible AI principles across all financial solution designs.
Required Knowledge & Experience
- AI/ML Mastery: Strong knowledge of AI techniques and tools, with demonstrated experience applying Gen AI/LLMs to specific financial or corporate use cases.
- Regulated Delivery: Proven track record of delivering production-grade solutions within highly regulated organizations (e.g., Tier 1 Banks or Government).
- Advanced Orchestration: Knowledge of Agentic Workflows and orchestration frameworks to drive automated decisioning and complex system behaviours.
- Data Intensive Expertise: Deep understanding of data modeling, cloud-native architectures, and big application development within a banking tech ecosystem.
- Security & Vetting: Must hold and maintain an active SC Clearance.
Solution Architect/ AI Manager in Oxford employer: Randstad Digital
As a leading employer in the financial technology sector, we offer an innovative work environment where creativity and technical expertise thrive. Our commitment to employee growth is reflected in our robust training programmes and opportunities for advancement, particularly in AI and data architecture. Located in a vibrant city, we foster a collaborative culture that values diversity and encourages the exploration of cutting-edge technologies, making us an ideal place for professionals seeking meaningful and impactful careers.
StudySmarter Expert Advice🤫
We think this is how you could land Solution Architect/ AI Manager in Oxford
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at events. We all know that sometimes it’s not just what you know, but who you know that can get you in the door.
✨Tip Number 2
Prepare for those interviews by practising common questions and scenarios related to AI and data architecture. We recommend doing mock interviews with friends or using online platforms to boost your confidence.
✨Tip Number 3
Showcase your projects! Whether it’s a portfolio or a GitHub repository, having tangible examples of your work can really set you apart. We love seeing how you’ve applied your skills in real-world situations.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we’re always on the lookout for passionate candidates like you!
We think you need these skills to ace Solution Architect/ AI Manager in Oxford
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the job description. Highlight your AI/ML mastery and any relevant projects you've worked on, especially in regulated environments like banks.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're the perfect fit for the AI Solution Architect role. Share specific examples of how you've led technical teams or delivered innovative solutions in the past.
Showcase Your Technical Skills:Don’t just list your skills; demonstrate them! Include details about your experience with cloud engineering, data architecture, and any tools you've used in AI/ML projects. We want to see your technical prowess!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into our hands quickly, especially since we expect a high volume of applications!
How to prepare for a job interview at Randstad Digital
✨Know Your Tech Inside Out
Make sure you’re well-versed in AI techniques and tools, especially those relevant to financial applications. Brush up on your knowledge of Gen AI and LLMs, as you’ll likely be asked how you’ve applied these in past projects.
✨Blueprint Your Ideas
Prepare to discuss how you would create technical blueprints for data pipelines. Think about specific examples where you’ve designed scalable solutions and be ready to explain your thought process and the outcomes.
✨Showcase Your Leadership Skills
Be ready to talk about your experience in providing strategic direction across engineering teams. Highlight instances where you’ve enforced best practices in DevOps/MLOps and how that led to successful project delivery.
✨Translate Complexity into Simplicity
Practice explaining complex technical concepts in simple terms. You might be asked to translate business requirements into actionable plans, so think of examples where you’ve successfully done this in the past.
