Databricks AI Architect

Capgemini; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Hybrid working

Flexible working arrangements

Training and certifications

Job summary

Capgemini UK is seeking a Data & AI Solution Architect to design and lead delivery of intelligent data platforms and AI-native solutions, unlocking advanced analytics, GenAI, and autonomous decision-making at scale.

You will work with Databricks Lakehouse, Azure AI, and emerging agentic frameworks to modernise data and AI capabilities, translating business strategy into governed architectures.

Qualifications

• Proven experience designing data and AI platforms with Databricks.
• Strong knowledge of Databricks Lakehouse, Unity Catalog, MLflow and AI workloads.
• Experience building GenAI solutions (RAG, embeddings, LLM integration).
• Experience designing agentic workflows and orchestration patterns.
• Strong Azure AI integration with Databricks and modern tooling.

Responsibilities

• Design scalable, secure Databricks Lakehouse architectures unifying data, analytics, and AI.
• Use GenAI and tooling to accelerate delivery, producing pipelines, infra, and business logic.
• Build enterprise-grade data pipelines and AI workflows with reusable patterns.
• Embed GenAI capabilities like RAG, vector search, and AI assistants into data platforms.
• Design and orchestrate AI agents and multi-agent workflows for intelligent automation.
• Apply MLOps and LLMOps to ensure scalable, maintainable AI solutions.
• Monitor and optimize platform performance, cost, and model effectiveness.
• Collaborate with engineering, data, and business teams for end-to-end delivery.
• Stay ahead of Databricks AI and Azure ecosystem capabilities and apply to use cases.

Skills

Databricks

GenAI

AI workloads

MLOps

Azure AI

Data platforms

CI/CD

VS Code

GitHub Copilot

Team leadership

Tools

Databricks Lakehouse

Unity Catalog

MLflow

VS Code

GitHub Copilot

Job description

Who You'll Be Working With

As a Data & AI Solution Architect at Capgemini, you will design and lead the delivery of intelligent data platforms and AI-native solutions that unlock advanced analytics, GenAI, and autonomous decision-making at scale. You will translate business strategy into AI-ready, governed architectures and take ownership from data foundations through to AI-driven outcomes.

You will work within the Data Platforms team, at the forefront of Databricks Lakehouse, Azure AI, and emerging agentic frameworks, helping clients modernise and transform their data and AI capabilities.

Security Clearence

To be successfully appointed to this role, must be eligible to obtain Security Check (SC)clearance.

To obtain SC clearance, the successful applicant must have resided continuously within the United Kingdom for the last 5 years, along with other criteria and requirements.

Throughout the recruitment process, you will be asked questions about your security clearance eligibility such as, but not limited to, country of residence and nationality.

Some posts are restricted to sole UK Nationals for security reasons; therefore, you may be asked about your citizenship in the application process.

The Focus Of Your Role

You will shape next-generation data and AI platforms by combining deep Databricks expertise with modern engineering practices. Using tools such as VS Code and AI-assisted development, you will rapidly design, build, and scale enterprise solutions while continuously bringing new innovations into delivery.

Key Responsibilities Include

• Design scalable, secure Databricks Lakehouse architectures that unify data, analytics, and AI.
• Use GenAI and developer tooling to accelerate delivery, generating production-ready pipelines, infrastructure, and business logic.
• Build enterprise-grade data pipelines and AI workflows using reusable, governed patterns.
• Embed GenAI capabilities including RAG, vector search, and AI assistants into data platforms.
• Design and orchestrate AI agents and multi-agent workflows to enable intelligent automation.
• Apply MLOps and LLMOps practices to ensure AI solutions are scalable and maintainable.
• Monitor and optimise platform performance, cost, and model effectiveness.
• Collaborate with engineering, data, and business teams to deliver end-to-end solutions.
• Stay ahead of emerging capabilities across Databricks AI and Azure agentic ecosystems and apply them to real-world use cases.

What You'll Bring

You will bring strong experience in delivering modern data and AI platforms, with a focus on scalable, governed solutions. You will be confident using AI-assisted development approaches to improve delivery speed and quality.

You will be able to translate business requirements into practical data and AI architectures, establish reusable engineering patterns, and lead teams towards automation-first approaches while ensuring security, governance, and responsible AI practices are maintained.

Experience

• Proven experience designing and delivering data and AI platforms using Databricks.
• Strong knowledge of Databricks Lakehouse, Unity Catalog, MLflow, and AI workloads.
• Experience developing GenAI solutions such as RAG, embeddings, and LLM integration.
• Experience designing agentic workflows and orchestration patterns.
• Strong understanding of Azure AI services and their integration with Databricks.
• Experience using VS Code and AI-assisted development tools such as GitHub Copilot.
• Proven ability to accelerate SDLC using automation, templates, and standardised engineering approaches.
• Experience implementing CI/CD pipelines and infrastructure as code.
• Strong communication, stakeholder engagement, and leadership skills.

Key Differentiators

• Actively explores and brings new ideas from the Databricks AI and Azure ecosystem into delivery.
• Uses GenAI and developer tooling to improve productivity and solution quality.
• Focuses on reusable, scalable patterns rather than one-off implementations.
• Understands how AI can transform both business processes and the software development lifecycle.
• Brings a strong perspective on enterprise AI adoption, governance, and architecture.

Additional Info

Hybrid working: 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.

If you are successfully offered this position, you will go through a series of pre-employment checks, including identity, nationality (single or dual) or immigration status, employment history going back 3 continuous years, and unspent criminal record check (known as Disclosure and Barring Service)

What We'll Offer You

You will be encouraged to have a positive work-life balance. Our hybrid-first way of working means 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.

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.

Why we're different

At Capgemini, we help organisations across the world become more agile, more competitive, and more successful. Smart, tailored, often ground‑breaking technical solutions to complex problems are the norm. But so, too, is a culture that’s as collaborative as it is forward thinking. Working closely with each other, and with our clients, we get under the skin of businesses and to the heart of their goals. You will too.

Capgemini is proud to represent nearly 130 nationalities and its cultural diversity. Our holistic definition of diversity extends beyond gender, gender identity, sexual orientation, disability, ethnicity, race, age, and religion. Capgemini views diversity as everything that makes us who we are as an organization, including our social background, our experiences in life and work, our communication styles and even our personality. These dimensions contribute to the type of diversity we value the most: diversity of thought.