At a Glance
- Tasks: Design and operationalise advanced AI systems, bridging prototypes to business solutions.
- Company: Capgemini Invent, a leader in inventive transformation consulting.
- Benefits: Flexible working, competitive salary, and a focus on employee wellbeing.
- Why this job: Join a team of innovators and make a real impact with cutting-edge technology.
- Qualifications: Experience in AI/ML solutions and cloud-native architectures required.
- Other info: Dynamic environment with opportunities for personal and professional growth.
The predicted salary is between 36000 - 60000 £ per year.
At Capgemini Invent, we believe difference drives change. As inventive transformation consultants, we blend our strategic, creative and scientific capabilities, collaborating closely with clients to deliver cutting-edge solutions. Join us to drive transformation tailored to our client's challenges of today and tomorrow. Informed and validated by science and data. Superpowered by creativity and design. All underpinned by technology created with purpose.
We’re seeking an AI engineer who can design, build, and operationalise advanced AI, Machine Learning, and Generative AI systems at enterprise scale. The focus of this role is to bridge the gap between AI prototypes and embedding data and AI solutions in business. You’ll scale AI solutions responsibly and reliably, ensuring they move from lab to live by building the right solutions, practices, and guardrails while ensuring business value creation and impact.
YOUR ROLEIn this position you will play a key part in:
- Assessing and implementing robust MLOps framework, governance and best practices as per industry standards
- Designing and delivering end-to-end AI/ML systems, from data preparation and model development to model deployment, feature stores, model management and monitoring
- Delivering solutions using the latest GenAI and Agentic Frameworks, such as ADK, Langgraph, Microsoft Agent Framework, Llamaindex and others
- Translating AI use case requirements into data and AI architectures using the most suitable cloud services across hyperscalars
- Architecting and implementing Generative AI solutions, including RAG pipelines, agentic workflows, and orchestration of large language models across Azure, GCP, or AWS
- Embedding safety, evaluation, and assurance mechanisms across the AI lifecycle, ensuring solutions are ethical, explainable, and responsible
- Translating business and functional requirements into technical blueprints and guiding multi-disciplinary teams to execute them
- Collaborating with Product Managers, Data Scientists and Business stakeholders to ensure AI solutions drive business value and impact
As part of your role, you will also have the opportunity to contribute to the business and your own personal growth, through activities that form part of the following categories:
- Business Development - Build client-ready demos/POVs, support proposals and technical deep-dives, and showcase delivery patterns
- Internal contribution - Build reusable assets and frameworks that accelerate delivery across accounts, shape frameworks for Capgemini’s Data & AI Innovation team, support capability development by contributing to our internal communities and best practices
- Capability Development - Contribute to thought leadership, blog posts, or internal accelerator development in emerging AI engineering topics such as Agentic AI, LLMOps, or evaluation frameworks
We’d love to meet someone with:
- Experience working in a major Consulting firm, and/or in industry but having a Consulting mindset with a proven ability to be successful in a matrixed organisation, and to enlist support and commitment from peers in selling and delivering solutions
- Experience of designing and implementing MLOPs strategy and framework and proven track record in designing and delivering AI/ML solutions at scale, from concept to production
- Deep understanding of Generative AI and Agentic AI — RAG pipelines, embeddings, evaluation harnesses, and orchestration frameworks
- Experience designing cloud-native data and AI architectures across Azure, GCP, AWS and/or Databricks
- The ability to demonstrate the potential that scaling AI unlocks business value and impact
This list shows the technologies we work with most often. We don’t expect you to have experience in all of them - what matters is a strong foundation and a good cross-section of these skills, along with the adaptability and curiosity to learn new tools as projects demand. We like to innovate and need self-driven, fast-paced learners in our team.
- Experience with at least one major cloud platform: Azure (Foundry, AI Studio, OpenAI, AKS), GCP (Vertex AI, Cloud Run), AWS (Bedrock, SageMaker)
- Experience building and automating AI/ML pipelines using tools such as MLflow, Kubeflow, Azure ML, Vertex Pipelines, Airflow or Google ADK
- Hands-on experience with Generative and Agentic AI frameworks such as LangChain, LlamaIndex, CrewAI, Autogen, Google ADK, or similar
- Ability to design and implement RAG pipelines, agentic workflows, MCP and integration with LLM APIs (OpenAI, Anthropic, Hugging Face OR similar)
- Proficiency in CI/CD and containerisation: GitHub Actions, Azure DevOps, Docker, Kubernetes
- Familiarity with evaluating AI system performance, including prompt evaluation, A/B testing, and quality assessment frameworks
- Understanding of modern data patterns: lakehouse architectures, vector databases, and relational/NoSQL stores
- Familiarity with API gateways, event streaming and general integration patterns
You need to have resided in the UK for the last 5 years to be able to apply for this role.
We’re a fantastic team of bright, ambitious people who love bringing the latest tech to real clients in production to make a meaningful difference. We work across both the public and private sectors, and our impact is tangible because we innovate, we deploy, and you will see your work come to life in the real world.
Technology moves fast, and so do we. We’re a group of true tech enthusiasts who push boundaries, experiment freely, and are trusted at Capgemini to explore what comes next. Our in-house projects highlight what’s possible with the newest models and agentic frameworks, and we regularly showcase our work at major events and conferences – and then we bring it to our clients to bring it to life, completing the full innovation tech cycle.
We’re looking for more people with the curiosity, drive, and self-starting spirit of real innovators, people who love technology and want to build the future with us.
We are delighted to have received the “Glassdoor Best Places to work UK’ accolade for 5 consecutive years. To see what it’s like to work at Capgemini Invent, visit our Glassdoor page.
At Capgemini we don’t just believe in Diversity & Inclusion, we actively go out to making it a working reality. Driven by our core values and Active Inclusion Campaign, we build environments where you can bring your whole self to work.
We aim to build an environment where employees can enjoy a positive work-life balance. We embed hybrid working in all that we do and make flexible working arrangements the day-to-day reality for our people. All UK employees are eligible to request flexible working arrangements.
Employee wellbeing is vitally important to us as an organisation. We see a healthy and happy workforce a critical component for us to achieve our organisational ambitions. To help support wellbeing we have trained ‘Mental Health Champions’ across each of our business areas. We have also invested in wellbeing apps such as Thrive and Peppy.
We’re also focused on using tech to have a positive social impact. So, we’re working to reduce our own carbon footprint and improve everyone’s access to a digital world. It’s something we’re really serious about. In fact, we were even named as one of the world’s most ethical companies by the Ethisphere Institute for the 10th year.
AI Engineering Consultant / Senior Consultant in Manchester employer: Capgemini
Contact Detail:
Capgemini Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Engineering Consultant / Senior Consultant in Manchester
✨Tip Number 1
Network like a pro! Get out there and connect with people in the AI and consulting space. Attend industry events, webinars, or even local meetups. You never know who might have the inside scoop on job openings or can refer you to someone at Capgemini.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those that demonstrate your experience with Generative AI and MLOps. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your experience with cloud platforms and AI frameworks. Practice common interview questions and think about how you can relate your past experiences to the role at Capgemini.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team at Capgemini Invent.
We think you need these skills to ace AI Engineering Consultant / Senior Consultant in Manchester
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the AI Engineering Consultant role. Highlight your relevant experience with AI, MLOps, and cloud platforms like Azure or AWS. We want to see how your skills align with our needs!
Showcase Your Projects: Include specific examples of projects you've worked on that demonstrate your expertise in AI and machine learning. We love seeing real-world applications of your skills, so don’t hold back on the details!
Be Authentic: Let your personality shine through in your application. We value diversity and want to know what makes you unique. Share your passion for technology and innovation, and how you can contribute to our team.
Apply Through Our Website: For the best chance of success, make sure to apply directly through our website. This helps us keep track of your application and ensures it gets the attention it deserves. We can't wait to hear from you!
How to prepare for a job interview at Capgemini
✨Know Your AI Stuff
Make sure you brush up on the latest trends in AI, especially around Generative AI and MLOps. Be ready to discuss specific frameworks like LangChain or Azure ML, and how you've used them in past projects. This shows you're not just familiar with the theory but can apply it practically.
✨Showcase Your Problem-Solving Skills
Prepare to share examples of how you've tackled complex AI challenges in previous roles. Use the STAR method (Situation, Task, Action, Result) to structure your answers. This will help interviewers see your thought process and how you can bridge the gap between AI prototypes and real-world applications.
✨Understand the Business Impact
Be ready to explain how your AI solutions have driven business value in the past. Discuss metrics or outcomes that demonstrate your impact. This is crucial for a role that focuses on embedding AI into business processes, so make sure you can articulate this clearly.
✨Engage with the Interviewers
Don’t just wait for questions; engage with your interviewers. Ask insightful questions about their current projects or challenges they face. This shows your genuine interest in the role and helps you assess if the company is the right fit for you too.