At a Glance
- Tasks: Shape the future of data and AI for top financial institutions.
- Company: Join AWS, the leading cloud platform innovating in financial services.
- Benefits: Enjoy flexible work-life balance, mentorship, and career growth opportunities.
- Other info: Diverse team culture that values unique experiences and perspectives.
- Why this job: Make a real impact by designing AI-ready data architectures for global clients.
- Qualifications: Master's or Bachelor's in relevant fields; experience in IT development preferred.
The predicted salary is between 81000 - 99000 £ per year.
Shape the future of data and AI for the world's largest and most complex financial institutions. As a Specialist Data & AI Solutions Architect within our Global Financial Services (GFS) organisation, you'll work with a focused portfolio of strategic accounts across EMEA and APJ, designing the data foundations, governance frameworks, and AI-ready architectures that enable tier-one financial services customers to move from experimentation to production-grade agentic and generative AI systems at enterprise scale. This is not a high-volume role. You'll go deep, not wide — building lasting technical relationships with a small number of the most significant financial services organisations in the world.
Key job responsibilities:
- Serve as the trusted technical advisor for data and AI strategy across a small number of the largest, most complex Global Financial Services accounts in EMEA and APJ.
- Design data architectures — lakehouses, knowledge graphs, vector stores, feature platforms, real-time pipelines — that form the foundation for agentic and generative AI, tailored to the regulatory, sovereignty, and resilience requirements of tier-one financial institutions.
- Guide customers on building AI-ready data estates: quality, lineage, governance, semantic layers, and retrieval frameworks that enable trustworthy AI grounding at scale.
- Advise on agentic system architecture — RAG, tool-use patterns, memory and state management, multi-agent orchestration, and human-in-the-loop guardrails — with attention to auditability, explainability, and compliance.
- Collaborate with account teams, GenAI specialists, and the broader specialist SA community to shape long-term strategies connecting data modernisation to AI value realisation.
- Engage at senior technical and executive levels, translating complex concepts into business-aligned recommendations that link data investment to measurable AI outcomes.
- Develop reference architectures and reusable assets addressing financial services patterns — regulatory-compliant RAG, multi-jurisdictional data mesh, real-time decisioning, and secure agent-to-data connectivity.
- Publish thought leadership content (whitepapers, blogs, workshops) on data foundations for AI and agentic system design in financial services.
- Partner with service teams (Bedrock, Q, Glue, Lake Formation, Redshift, OpenSearch, Neptune) and product groups to influence roadmap priorities based on customer needs.
- Stay current on emerging trends in data architecture, foundation models, and agentic AI frameworks, feeding insights into customer engagements and internal communities.
A day in the life: You'll join a focused, high-calibre group of specialist Solution Architects supporting the world's most important financial services customers. The team operates across regions on deeply technical, strategically significant engagements — solving problems that don't have off-the-shelf answers. Day-to-day, you'll design data platforms that underpin agentic AI workloads, review retrieval and grounding architectures, advise on governance models that satisfy regulators while enabling AI innovation, and help customers connect existing data investments to the AI outcomes their leadership demands. We value depth, intellectual curiosity, and a genuine desire to help customers succeed.
Basic qualifications:
- Master's degree or above in computer science, engineering, mathematics or equivalent, or Bachelor's degree in computer science, engineering, mathematics or equivalent.
- Experience in IT development or implementation/consulting in the software or Internet industries.
- Experience within specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics).
- Experience with data infrastructures: relational analytic DBMS, Elastic-Search, and Big Data EMR/EC2/Glue/Lambda, or experience with training and deploying machine learning systems to solve large-scale optimizations.
- Experience communicating across technical and non-technical audiences, including executive level stakeholders or clients.
Preferred qualifications:
- Experience working with Data & AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage.
- PhD in computer science, machine learning, engineering, or related fields, or experience with AWS services including S3, Redshift, Sagemaker, EMR, Kinesis, Lambda, and EC2.
- Knowledge of general AI tools.
- Knowledge of data engineering pipelines, cloud solutions, ETL management, databases, visualizations and analytical platforms.
- Experience with data analytics platforms (Power BI, Python, SQL, Tableau), or experience working with large-scale data mining and reporting tools (examples: SQL, MS Access, Essbase, Cognos) and other financial systems (examples: Oracle, SAP, Lawson, JD Edwards).
- Experience developing, deploying and managing AI products at scale.
- Experience with data governance, lineage, and quality frameworks in regulated industries — particularly financial services.
Specialist Data & AI SA, AWS Specialist & Partner Industries Organization (ASPI), Global Financial Services (GFS) in London employer: AmazonWebServices
At Amazon Web Services (AWS), we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. As a Senior Delivery Consultant (DevOps) in the UK, you'll have the opportunity to work closely with diverse clients, driving their cloud success while benefiting from extensive mentorship and professional growth opportunities. Our commitment to inclusion and employee empowerment ensures that every team member can thrive and contribute meaningfully to our mission of delivering cutting-edge cloud solutions.
StudySmarter Expert Advice🤫
We think this is how you could land Specialist Data & AI SA, AWS Specialist & Partner Industries Organization (ASPI), Global Financial Services (GFS) in London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like AmazonWebServices!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Specialist Data & AI SA, AWS Specialist & Partner Industries Organization (ASPI), Global Financial Services (GFS) at AmazonWebServices.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like AmazonWebServices.
✨Apply Directly through Our Website
When you find a suitable opening like Specialist Data & AI SA, AWS Specialist & Partner Industries Organization (ASPI), Global Financial Services (GFS) at AmazonWebServices, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Specialist Data & AI SA, AWS Specialist & Partner Industries Organization (ASPI), Global Financial Services (GFS) 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!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at AmazonWebServices, 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 AmazonWebServices. 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 AmazonWebServices
✨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!
✨Showcase Your Projects
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
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at AmazonWebServices!
✨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.