At a Glance
- Tasks: Design innovative data architectures and guide AI strategies for top financial services clients.
- Company: Join AWS, the leading cloud platform, supporting major global financial services.
- Benefits: Competitive salary, inclusive culture, mentorship, and opportunities for career growth.
- Other info: Collaborative environment that values diversity, curiosity, and continuous learning.
- Why this job: Make a real impact in AI and data architecture while working with cutting-edge technology.
- Qualifications: Masters or Bachelors in relevant fields, plus experience in IT development and data technologies.
The predicted salary is between 63000 - 103000 £ per year.
Requirements
- Masters degree or above in computer science, engineering, mathematics or equivalent, or Bachelors 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 such as software development, cloud computing, systems engineering, infrastructure, security, networking, or data & analytics
- Experience with data infrastructures such as relational analytic DBMS, Elastic-Search, and Big Data EMR/EC2/Glue/Lambda, or experience 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
- Experience working with Data & AI related technologies, including AI/ML, Gen AI, Analytics, Database, and/or Storage
- Ph D 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 such as Power BI, Python, SQL, Tableau, or experience working with large-scale data mining and reporting tools and other financial systems
- Experience developing, deploying, and managing AI products at scale
- Experience with data governance, lineage, and quality frameworks in regulated industries, particularly financial services
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 such as lakehouses, knowledge graphs, vector stores, feature platforms, and real-time pipelines that form the foundation for agentic and generative AI, tailored to regulatory, sovereignty, and resilience requirements
- Guide customers on building AI-ready data estates, including quality, lineage, governance, semantic layers, and retrieval frameworks that enable trustworthy AI grounding at scale
- Advise on agentic system architecture, including 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, Gen AI 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 such as regulatory-compliant RAG, multi-jurisdictional data mesh, real-time decisioning, and secure agent-to-data connectivity
- Publish thought leadership content including whitepapers, blogs, and workshops on data foundations for AI and agentic system design in financial services
- Partner with service teams 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
- Design data platforms that underpin agentic AI workloads
- Review retrieval and grounding architectures
- Advise on governance models that satisfy regulators while enabling AI innovation
- Help customers connect existing data investments to the AI outcomes their leadership demands
Technologies
- Agentic AI
- AI
- AWS
- Lambda
- Redshift
- Big Data
- Cloud
- ETL
- Machine Learning
- Power BI
- Python
- RAG
- SQL
- Security
- Tableau
- Open Search
- Architect
- Support
- Oracle
- SAP
- Web
More
We are AWS, the worlds most comprehensive and broadly adopted cloud platform, serving customers from innovative startups to Global 500 companies.
You will join a focused, high-calibre group of specialist Solution Architects supporting the worlds most important financial services customers across EMEA and APJ on deeply technical, strategically significant engagements.
We value diverse experiences, inclusion, mentorship, career growth, and work/life balance, and we offer a collaborative culture that encourages curiosity and continuous learning.
- last updated 36 week of 2026
- #J-18808-Ljbffr
Specialist Solutions Architect - Database, Data & AI employer: AmazonWebServices
At Amazon Web Services (AWS), we are committed to fostering a culture of innovation and inclusivity, making us an exceptional employer for those in the Site Reliability Engineering Services role. Our employees benefit from extensive mentorship and career growth opportunities, alongside a strong emphasis on work-life balance, ensuring that personal well-being is valued as much as professional success. Join us in building the future of cloud computing while being part of a team that celebrates diversity and encourages collaboration.
StudySmarter Expert Advice🤫
We think this is how you could land Specialist Solutions Architect - Database, Data & AI
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We think you need these skills to ace Specialist Solutions Architect - Database, Data & AI
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at AmazonWebServices.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at AmazonWebServices and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at AmazonWebServices
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If AmazonWebServices uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
