DevOps AI Platform Architect

Job Role: DevOps AI Platform Architecture

• Designing and implementing AI platform architectures using cloud services such as Microsoft Azure, AWS, or Google Cloud.
• Establishing CI/CD and MLOps pipelines to automate model training, testing, deployment, and monitoring.
• Managing containerized workloads using Docker and Kubernetes for scalability and reliability.
• Ensuring platform security, compliance, governance, and cost optimization through best practices and automation.
• Collaborating with data scientists, developers, security teams, and business stakeholders to deliver enterprise-grade AI solutions.
• Implementing observability, monitoring, and incident management processes to maintain platform performance and availability.
• Evaluating and integrating emerging technologies in Generative AI, platform engineering, and cloud-native ecosystems to drive innovation.

Location: London, UK

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.

As a DevOps AI Platform Architect, you will be designing, building, and optimizing scalable AI platforms that enable organizations to develop, deploy, and manage AI/ML solutions efficiently and securely. This role aligns with my passion for cloud computing, DevOps practices, automation, and artificial intelligence, allowing me to create robust platforms that accelerate innovation and business value.

• Define and document global AI platform patterns Discovery Zone BYOD end-to-end ML lifecycle reference architectures and obtain approvals through architecture forums
• Design Model Serving Architecture
• Partner with the AI Tech Lead on the Model Serving PoC and define the end-to-end architecture for scalable and secure model deployment
• Define MLOps Architecture
• Define and document MLOps architecture using learnings from the Model
• Serving PoC and drive approvals for standardization
• Enable LLM Strategic Capabilities
• Assess different capabilities for LLM Azure AI foundry Bedrock and Databricks and take design decisions for approval
• Work with security Data protection office other architecture teams to align them with the decision and secure approvals for roll out
• Document the low level design for LLM roll out to different use case
• Evolve Platform Capabilities
• Drive incremental platform capabilities Responsible AI GenAI Data Governance etc aligned with the approved L2 architecture

• You'd be joining an accredited Great Place to work for Wellbeing in 2024. 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, 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 ManageMentor, Cybersecurity qualifications and much more.
• You will be joining one of the World's Most Ethical Companies®, as recognised by Ethisphere® for 13 consecutive years. We live our values by making ethical business choices every day. Working ethically is at the centre of our culture at Capgemini, meaning you will be helping to create a future we can all be proud of.