Salary: £63,000 - 103,000 per year
Requirements: - We have extensive experience designing and architecting solutions on Google Cloud Platform across IaaS, PaaS, and SaaS environments.
- We have proven experience defining enterprise-scale migrations to Google Cloud, with a strong understanding of migration strategies including rehost, replatform, refactor, repurchase, retire, retain, and relocate.
- We have broad hands-on knowledge of core Google Cloud services across compute, containers, storage, databases, networking, security, observability, DevOps, and cost management.
- We have in-depth experience designing Google Cloud landing zones and cloud foundations, including resource hierarchy, projects, billing, IAM, shared VPC, hub-and-spoke networking, service perimeters, guardrails, logging, monitoring, governance, and security controls.
- We have experience architecting secure, scalable, and highly available cloud environments, including integration between on-premises infrastructure and Google Cloud.
- We have strong experience with containerised solutions, Kubernetes production platforms, microservices, and ideally Google Kubernetes Engine.
- We have experience deploying infrastructure using automation and Infrastructure as Code, particularly Terraform.
- We have experience designing AI-ready cloud and data platforms that support ingestion, storage, governance, analytics, model deployment, monitoring, and integration with enterprise applications.
- We understand generative AI solution patterns, such as retrieval-augmented generation, enterprise search, intelligent assistants, document processing, content generation, and AI-enabled workflow automation.
- We have awareness of AI governance, responsible AI, data privacy, security, model risk, auditability, and compliance considerations for AI-enabled cloud solutions.
- We have strong analytical and technical skills, with the ability to learn new tools, services, and methodologies as the market evolves.
- We can identify opportunities to use automation, AI-assisted engineering, AIOps, and cloud-native tooling to improve reliability, observability, delivery speed, and operational efficiency.
- We have excellent English verbal and written communication skills, with the ability to engage effectively with both technical and non-technical stakeholders.
- We can work well under pressure, respond quickly to client needs, and adapt to changing requirements.
- Good to have: pre-sales or commercial experience.
- Good to have: previous experience with on-premises infrastructure management.
- Good to have: comfort with Continuous Integration and Continuous Deployment concepts and common approaches using tools such as Jenkins, Git, Azure DevOps, GitHub Actions, GitLab CI/CD, Cloud Build, or Cloud Deploy.
- Good to have: experience with Anthos, Apigee, Cloud Composer, Dataflow, Pub/Sub, Looker, Vertex AI, Model Garden, Document AI, Gemini, or other Google Cloud data, analytics, API management, AI, or generative AI services.
- Good to have: experience designing retrieval-augmented generation architectures using vector search, embeddings, enterprise data sources, access controls, and secure application integration patterns.
- Good to have: experience with MLOps, including model lifecycle management, CI/CD for ML, feature stores, model monitoring, experimentation, and deployment pipelines.
- Good to have: experience with AIOps, intelligent observability, automated remediation, anomaly detection, and AI-assisted cloud operations.
- Good to have: experience with cloud security, compliance, and governance frameworks, including considerations specific to AI-enabled workloads.
- Good to have: Google Cloud certifications such as Professional Cloud Architect, Professional Cloud DevOps Engineer, Professional Cloud Security Engineer, Professional Cloud Network Engineer, Professional Data Engineer, Professional Machine Learning Engineer, or Associate Cloud Engineer.
Responsibilities: - We lead technical discussions with clients and design the best solutions for them.
- We use Google Cloud services to solve clients business and technology challenges as part of our day-to-day work.
- We help clients understand how cloud platforms can support AI adoption, including generative AI, machine learning, intelligent automation, AI-assisted operations, and responsible AI practices.
- We deliver cloud projects and help clients in their journey to Google Cloud.
- We contribute to technical definitions, assessments, workshops, and cloud migration implementations.
- We continuously look for opportunities to automate processes, remediate technical debt, improve operational efficiency, and identify areas where AI and automation can accelerate business outcomes.
- We contribute to internal innovation projects as well as client delivery.
Technologies: - AI
- API
- Apigee
- Architect
- Azure
- CI/CD
- Cloud
- Composer
- DevOps
- Git
- GitHub
- GitLab
- IAM
- IaaS
- Support
- Jenkins
- Kubernetes
- Looker
- Machine Learning
- MLOps
- Network
- PaaS
- Security
- Terraform
- microservices
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We are NTT DATA, a $30+ billion business and technology services, AI and digital infrastructure leader, co-innovating with clients and partners globally for business and societal impact. We serve 75% of the Fortune Global 100, employ experts in over 70 countries, and are a Global Top Employer backed by NTT Groups annual $3 billion+ R&D investment. We offer a highly innovative environment with opportunities to work across financial services, public sector, insurance, telco and media, alongside highly skilled engineers and cloud architects. We support learning and development, continuous growth, and flexible work options, and we are committed to equal opportunities, diversity, inclusion, and reasonable adjustments throughout the recruitment process.
last updated 36 week of 2026