At a Glance
- Tasks: Design and implement cutting-edge AI solutions in financial services and capital markets.
- Company: Join a leading recruitment agency in analytics with a focus on innovation.
- Benefits: Competitive salary, hybrid work model, and opportunities for professional growth.
- Other info: Collaborate with diverse teams and enjoy excellent career advancement opportunities.
- Why this job: Shape the future of AI in finance and make a real impact on transformation programmes.
- Qualifications: Strong background in AI, cloud, and data architecture with enterprise experience.
The predicted salary is between 72207 - 88253 £ per year.
Senior AI Solution Architects are required to support the design, implementation and scaling of advanced AI solutions within financial services and capital markets environments. This role would suit an experienced professional with a strong background in AI, cloud and data architecture, with experience designing enterprise AI solutions and translating business requirements into scalable technical architectures. You will play a key role in shaping AI architecture strategy, leading technical teams and supporting organisations as they move from strategy and experimentation through to enterprise deployment.
You will work closely with AI Engineers, Data Scientists, Enterprise Architects, MLOps teams, business stakeholders and senior leadership to design, deliver and scale AI solutions that drive measurable business outcomes.
Key responsibilities:- Translating business objectives into AI architecture strategies, roadmaps and scalable solution designs
- Designing and implementing end to end AI and ML architectures across enterprise environments
- Defining scalable, performant and cost optimised deployment patterns across cloud, containerised and GPU enabled environments
- Supporting AI implementation programmes from proof of concept through to enterprise deployment and optimisation
- Evaluating and selecting technologies across open source and commercial platforms
- Designing and integrating AI solutions into existing enterprise systems and applications
- Working with AI Engineers, Data Scientists and technical teams to support AI delivery and scaling initiatives
- Supporting AI governance, security, risk and regulatory considerations throughout the delivery lifecycle
- Supporting architecture governance, technical review boards and design authorities
- Building relationships with technical and business stakeholders across large scale transformation programmes
- Producing solution design documentation, implementation plans and technical proposals
- Providing technical leadership and mentoring within multidisciplinary teams
- Experience designing AI, ML or modern data architectures within enterprise environments
- Strong understanding of cloud platforms such as AWS, Azure, GCP, Databricks or similar technologies
- Experience architecting scalable AI and ML solutions across serverless, containerised or GPU enabled environments
- Experience with LLMs, prompt engineering, embeddings, semantic search and RAG patterns
- Exposure to vector databases and agent frameworks such as LangChain, LangGraph or similar technologies
- Understanding of MLOps, LLMOps and model lifecycle management principles
- Experience designing APIs and integrating AI solutions into enterprise environments
- Strong understanding of modern data architectures and platform design principles
- Experience presenting architectural designs to technical and business stakeholders
- Financial services experience within capital markets or broader banking environments
This is a strong opportunity for an AI architecture professional who wants to work on high impact AI and data transformation programmes within complex financial services environments.
AI Solution Architect - Senior Manager/Associate Director Capital Markets employer: All The Top Bananas
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StudySmarter Expert Advice🤫
We think this is how you could land AI Solution Architect - Senior Manager/Associate Director Capital Markets
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We think you need these skills to ace AI Solution Architect - Senior Manager/Associate Director Capital Markets
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 All The Top Bananas, 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 All The Top Bananas. 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 All The Top Bananas
✨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.
