Lead AI Engineer in Manchester

Lead AI Engineer in Manchester

Manchester Full-Time 43200 - 72000 ÂŁ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Design and build advanced AI systems that make a real-world impact.
  • Company: Join Capgemini, a leading tech innovator with a vibrant culture.
  • Benefits: Flexible working, competitive pay, and a focus on employee wellbeing.
  • Why this job: Be at the forefront of AI technology and shape the future.
  • Qualifications: Experience in AI/ML solutions and cloud platforms is essential.
  • Other info: Dynamic team environment with opportunities for personal and professional growth.

The predicted salary is between 43200 - 72000 ÂŁ per year.

We’re seeking a Lead 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.

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:

  • 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.
  • Leading multi-disciplinary teams to execute complex requirements.
  • 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.
  • Collaborating with Product Managers, Data Scientists and Business stakeholders to ensure AI solutions drive business value and impact.

What You Will Bring

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 working with client sponsors, both technical and non-technical, to collaboratively design requirements and build out 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.

Your Technical Expertise:

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 deploying and scaling AI solutions using 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.

Nice To Haves

  • 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.

Eligibility

You need to have resided in the UK for the last 5 years to be able to apply for this role.

About Capgemini

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.

Need To Know

We are delighted to have received the “Glassdoor Best Places to work UK” accolade for 5 consecutive years. 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. When you join Capgemini, you’ll join a team that does the right thing. Whilst you will have London, Manchester or Glasgow as an office base location, you must be fully flexible in terms of assignment location, as these roles may involve periods of time away from home at short notice. We offer a remuneration package which includes flexible benefits options for you to choose to suit your own personal circumstances and a variable element dependent grade and on company and personal performance.

Lead AI Engineer in Manchester employer: Capgemini Invent

Capgemini is an exceptional employer that fosters a vibrant work culture where innovation thrives and employees are empowered to make a meaningful impact. With a strong commitment to diversity, inclusion, and employee wellbeing, we offer flexible working arrangements and robust support systems, including trained Mental Health Champions and wellbeing apps. Our focus on personal growth and professional development, combined with the opportunity to work on cutting-edge AI technologies in major UK cities, makes Capgemini a fantastic place for ambitious individuals looking to shape the future of technology.
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Contact Detail:

Capgemini Invent Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Lead AI Engineer in Manchester

✨Tip Number 1

Network like a pro! Reach out to your connections in the AI and tech space. Attend meetups, webinars, or conferences where you can chat with industry folks. You never know who might have the inside scoop on job openings!

✨Tip Number 2

Show off your skills! Create a portfolio showcasing your AI projects, especially those involving Generative AI and MLOps. Share it on platforms like GitHub or your personal website. This gives potential employers a taste of what you can do!

✨Tip Number 3

Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice common interview questions related to AI and machine learning. We recommend doing mock interviews with friends or using online platforms to get comfortable.

✨Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search. So, hit that apply button and let’s get you in the door!

We think you need these skills to ace Lead AI Engineer in Manchester

AI System Design
Machine Learning
Generative AI
MLOps Strategy
Cloud Services (Azure, GCP, AWS)
Data Architecture
RAG Pipelines
Agentic Workflows
Model Deployment
AI/ML Pipeline Automation
CI/CD Practices
Containerisation (Docker, Kubernetes)
Collaboration with Stakeholders
Problem-Solving Skills
Adaptability

Some tips for your application 🫡

Tailor Your Application: Make sure to customise your CV and cover letter to highlight your experience with AI, Machine Learning, and Generative AI. We want to see how your skills align with the role of Lead AI Engineer, so don’t hold back on showcasing relevant projects!

Showcase Your Technical Skills: When detailing your technical expertise, focus on the cloud platforms and tools mentioned in the job description. We’re keen on seeing your hands-on experience with Azure, GCP, or AWS, so be specific about your achievements and contributions.

Highlight Collaboration Experience: Since this role involves working with multi-disciplinary teams, share examples of how you’ve successfully collaborated with Product Managers, Data Scientists, and other stakeholders. We love to see teamwork in action!

Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it shows you’re serious about joining our team at StudySmarter!

How to prepare for a job interview at Capgemini Invent

✨Know Your AI Stuff

Make sure you brush up on the latest in AI, Machine Learning, and Generative AI. 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 buzzwords but can actually apply them.

✨Showcase Your Problem-Solving Skills

Prepare to share examples of how you've tackled complex AI challenges. Think about times when you had to bridge the gap between prototypes and real-world applications. Highlight your experience in designing and implementing MLOps strategies to demonstrate your hands-on expertise.

✨Collaborate Like a Pro

Since this role involves working with multi-disciplinary teams, be ready to talk about your collaboration skills. Share stories where you worked closely with Product Managers or Data Scientists to deliver impactful AI solutions. This will show that you can communicate effectively across different areas.

✨Understand Business Value

It's crucial to convey how AI can drive business value. Prepare to discuss how your previous projects have created tangible impacts for clients. This will help interviewers see that you not only understand the tech but also its application in a business context.

Lead AI Engineer in Manchester
Capgemini Invent
Location: Manchester

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