At a Glance
- Tasks: Deploy and optimise AI solutions across AWS and Azure while ensuring security and scalability.
- Company: Join a leading tech company recognised for its commitment to wellbeing and innovation.
- Benefits: Flexible work locations, extensive training opportunities, and mental health support.
- Other info: Great career growth potential with access to 250,000 courses and certifications.
- Why this job: Be at the forefront of AI technology and make a real impact in a dynamic environment.
- Qualifications: 5+ years in DevOps, strong cloud experience, and proficiency in Python.
The predicted salary is between 63000 - 77000 £ per year.
Описание
We are seeking a highly skilled AI Cloud Dev Ops & Platform Engineer who is responsible for the deployment, operation and continuous optimisation of AI, Machine Learning and Generative AI solutions across AWS and Azure.
Combining AIOps, Platform Engineering and Dev Ops capabilities, the role ensures AI platforms are secure, scalable, resilient and production ready.
Задачи
- Deploy, operate and support AI, ML and Generative AI solutions across AWS and Azure.
- Implement and manage LLM, RAG, AI Agent and Copilot-based solutions.
- Build and maintain CI/CD pipelines, infrastructure automation and operational tooling.
- Monitor platform health, model performance, reliability and operational SLAs.
- Troubleshoot incidents, perform root cause analysis and drive service improvements.
- Support AI governance, security, compliance and Responsible AI requirements.
- Collaborate with architects, engineers and business stakeholders to operationalise AI solutions.
- Contribute to AI platform strategy, standardisation and adoption of best practices.
Требования
- 5+ Years on Dev Ops & Platform Engineering.
- 3+ on AI Ops.
- Strong experience with Azure and/or AWS cloud platforms.
- Hands-on experience supporting AI, ML or Generative AI solutions in production.
- Knowledge of Azure Open AI, Azure AI Services, Amazon Bedrock and/or Sage Maker.
- Understanding of LLMs, RAG architectures, AI Agents and modern AI patterns.
- Experience in Platform Engineering, Dev Ops and cloud operations.
- CI/CD, Infrastructure as Code (Terraform, Bicep, Cloud Formation) and automation expertise.
- Proficiency in Python and scripting.
- Experience with Docker, Kubernetes, Git Hub Actions and/or Azure Dev Ops.
- Knowledge of monitoring, observability, reliability engineering and operational support.
- Будет плюсом: Lang Chain, Semantic Kernel, Crew AI or Auto Gen; Vector databases and AI orchestration frameworks; Databricks, Microsoft Fabric or enterprise data platforms; MLOps, Model Ops and AIOps practices; Experience in regulated or large-scale enterprise environments; Consulting experience delivering cloud, platform or AI transformation initiatives; Azure AI Engineer Associate; Azure Dev Ops Engineer Expert; AWS AI Practitioner; AWS Machine Learning Engineer / Specialty; AWS Dev Ops Engineer Professional; Kubernetes (CKA/CKAD)
Условия
The places that you work from day to day will vary according to your role, your needs, and those of the business; it will be a blend of Company offices, client sites, and your home; noting that you will be unable to work at home 100% of the time.
- You'd be joining an accredited Great Place to work for Wellbeing in 2024.
- To help support wellbeing we have trained 'Mental Health Champions' across each of our business areas, and we have invested in wellbeing apps such as Thrive and Peppy.
- You will be empowered to explore, innovate, and progress.
- You will benefit from Capgemini's 'learning for life' mindset, meaning you will have countless training and development opportunities from thinktanks to hackathons, and access to 250,000 courses with numerous external certifications from AWS, Microsoft, Harvard Manage Mentor, Cybersecurity qualifications and much more.
- #J-18808-Ljbffr
AI cloud DevOps & platform engineer employer: Capgemini
Capgemini is an excellent employer, offering a dynamic work culture that fosters collaboration and innovation in the heart of London. With a hybrid working model, employees enjoy the flexibility of blending office, client site, and home working, while also benefiting from extensive growth opportunities and professional development within the Capital Markets sector. Join us to be part of a team that values governance excellence and empowers you to make a meaningful impact in complex programme environments.
StudySmarter Expert Advice🤫
We think this is how you could land AI cloud DevOps & platform engineer
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Capgemini or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Capgemini.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Capgemini.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Capgemini that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace AI cloud DevOps & platform engineer
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 Capgemini.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Capgemini 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 Capgemini
✨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 Capgemini 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.
