AI cloud DevOps & platform engineer

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

Benefits offered by this job

Great Place to Work Wellbeing 2024

Mental Health Champions

Wellbeing apps Thrive & Peppy

250,000 courses with external certs

Job summary

Capgemini is seeking a highly skilled AI Cloud DevOps & Platform Engineer to deploy, operate and optimise AI/ML and Generative AI solutions across AWS and Azure. The role blends AIOps, Platform Engineering and DevOps to keep AI platforms secure, scalable and production-ready.

You will build CI/CD pipelines, automate infrastructure and support governance, security and Responsible AI practices while collaborating with architects and business stakeholders to operationalise AI at scale.

Qualifications

• 5+ years in DevOps and Platform Engineering.
• 3+ years in AI Ops or similar AI/ML ops.
• Strong hands-on experience with Azure and/or AWS cloud platforms.
• Production support for AI/ML/Generative AI solutions.
• Knowledge of Azure OpenAI, Azure AI Services, Bedrock or SageMaker.

Responsibilities

• Deploy, operate and support AI/ML/Generative AI solutions on AWS and Azure.
• Implement LLM, RAG, AI Agent and Copilot-based solutions.
• Build and maintain CI/CD pipelines and automation tooling.
• Monitor platform health, model performance and SLAs.
• Troubleshoot incidents and drive service improvements.
• Support governance, security and Responsible AI requirements.
• Collaborate with architects and stakeholders to operationalise AI solutions.
• Contribute to platform strategy and best-practice adoption.

Skills

DevOps

Platform Engineering

AI Ops

Azure

AWS

CI/CD

Terraform

Bicep

Python

Docker

Kubernetes

GitHub Actions

Azure DevOps

Tools

Terraform

Bicep

CloudFormation

Docker

Kubernetes

GitHub Actions

Azure DevOps

Job description

Описание:

We are seeking a highly skilled AI Cloud DevOps & 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 DevOps 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 DevOps & 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 OpenAI, Azure AI Services, Amazon Bedrock and/or SageMaker.
• Understanding of LLMs, RAG architectures, AI Agents and modern AI patterns.
• Experience in Platform Engineering, DevOps and cloud operations.
• CI/CD, Infrastructure as Code (Terraform, Bicep, CloudFormation) and automation expertise.
• Proficiency in Python and scripting.
• Experience with Docker, Kubernetes, GitHub Actions and/or Azure DevOps.
• Knowledge of monitoring, observability, reliability engineering and operational support.
• Будет плюсом: LangChain, Semantic Kernel, CrewAI or AutoGen; Vector databases and AI orchestration frameworks; Databricks, Microsoft Fabric or enterprise data platforms; MLOps, ModelOps 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 DevOps Engineer Expert; AWS AI Practitioner; AWS Machine Learning Engineer / Specialty; AWS DevOps 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.