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For Companies At a Glance
- Tasks: Lead AI projects in the Financial Services sector, optimising models and integrating solutions.
- Company: Capgemini is a global leader in tech transformation, empowering businesses towards a sustainable future.
- Benefits: Enjoy a collaborative work culture, career growth opportunities, and a chance to make a real impact.
- Why this job: Join a diverse team and shape the future of AI in a meaningful way.
- Qualifications: Experience with Azure AI Foundry, LLMs, Python, and AI security is essential.
- Other info: Be part of a company with over 55 years of trusted expertise and innovation.
The predicted salary is between 48000 - 72000 £ per year.
Get The Future You Want! Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.
Your Role
We are seeking a talented and experienced Azure AI Architect to join our team at Capgemini FS. In this role, you will be responsible for leading the delivery of projects within the Financial Services industry. The ideal candidate will have a strong background in the following:
- Design, develop, and optimize AI models using Azure AI Foundry, LLMs, and Azure machine learning services.
- Enhance and scale AI Platform, integrating RAG, LLMs, and ML pipelines into real-world applications.
- Develop AI agents with Azure AI Foundry, leveraging open standards such as MCP and A2A as well as principles of Multi-Agent Systems.
- Work closely with engineering teams to implement best practices in AI deployment, security, and performance.
- Collaborate with clients to understand business needs and transform them into scalable AI-driven solutions.
- Ensure seamless integration with Azure services, including Cognitive Services, OpenAI models, and vector databases.
Your Profile
- Proven experience working with Azure AI Foundry and its ecosystem.
- Strong background in LLM fine-tuning, RAG (Retrieval-Augmented Generation), and AI-driven application development.
- Proficiency in Python, ML frameworks (PyTorch, TensorFlow), and cloud-native AI solutions.
- Hands-on experience with Azure Cognitive Services, OpenAI APIs, and vector search (e.g., Azure AI Search, FAISS, CosmosDB, Pinecone, etc.).
- Experience in AI security, MLOps, and deploying scalable AI solutions.
- Ability to troubleshoot and optimize AI models for performance and accuracy.
About Capgemini
Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than fifty countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fuelled by its market-leading capabilities in AI, cloud, and data, combined with its deep industry expertise and partner ecosystem.
Azure AI Architect employer: Capgemini
Contact Detail:
Capgemini Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Azure AI Architect
✨Tip Number 1
Familiarise yourself with the latest Azure AI tools and technologies. Make sure you understand how Azure AI Foundry, LLMs, and machine learning services work, as this knowledge will be crucial during interviews and discussions with potential employers.
✨Tip Number 2
Network with professionals in the AI and Azure communities. Attend meetups, webinars, or conferences related to Azure AI to connect with industry experts and learn about the latest trends, which can give you an edge when applying for the role.
✨Tip Number 3
Showcase your hands-on experience with relevant projects. Whether it's through a portfolio or GitHub, demonstrate your proficiency in Python, ML frameworks, and Azure services by sharing examples of your work that align with the job requirements.
✨Tip Number 4
Prepare for technical interviews by practising problem-solving scenarios related to AI model optimisation and deployment. Being able to discuss real-world applications and solutions you've developed will help you stand out as a candidate.
We think you need these skills to ace Azure AI Architect
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in Azure AI Foundry, LLMs, and machine learning services. Use specific examples that demonstrate your skills in developing and optimising AI models.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for AI and your understanding of the Financial Services industry. Mention how your background aligns with the responsibilities outlined in the job description.
Highlight Technical Skills: Clearly list your technical skills, especially in Python, ML frameworks, and Azure services. Provide context on how you've applied these skills in previous roles to solve real-world problems.
Showcase Collaboration Experience: Emphasise any experience you have working with engineering teams or clients. Highlight your ability to translate business needs into scalable AI solutions, as this is crucial for the role.
How to prepare for a job interview at Capgemini
✨Showcase Your Technical Skills
Make sure to highlight your experience with Azure AI Foundry, LLMs, and machine learning services. Be prepared to discuss specific projects where you've designed, developed, or optimised AI models, as this will demonstrate your hands-on expertise.
✨Understand the Financial Services Sector
Since the role is within the Financial Services industry, it's crucial to familiarise yourself with the unique challenges and opportunities in this sector. Research recent trends and how AI can address these needs, so you can speak knowledgeably during the interview.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills and ability to apply your knowledge in real-world situations. Think of examples where you've integrated AI solutions into applications, focusing on the impact and results of your work.
✨Emphasise Collaboration and Communication
As the role involves working closely with engineering teams and clients, be ready to discuss your experience in collaborative environments. Highlight instances where you've successfully communicated complex technical concepts to non-technical stakeholders.
