Platform Engineer

AI teams need a platform they can build on confidently: secure access to data, repeatable environments and infrastructure that remains reliable as usage grows.

SR2 Consulting is looking for a hands-on Platform Engineer to help establish those foundations within a financial-services organisation building its internal AI capability.

You'll work closely with AI engineers, architecture, security and operations teams to create a practical platform for developing and running enterprise AI applications. The role offers scope to shape reusable services and engineering standards from an early stage.

• Build and maintain cloud environments that support AI development, testing and production workloads.

• Create reusable infrastructure modules and deployment patterns that make approved environments straightforward to provision.

• Configure identity, service permissions, networking, secrets management and encryption.

• Enable secure connectivity between AI applications, enterprise systems and data services, including Snowflake.

• Support containerised workloads and managed cloud services, choosing approaches appropriate to operational needs.

• Establish platform monitoring, capacity management, recovery procedures and cost visibility.

• Work with security teams to embed controls into platform design and configuration.

• Produce clear documentation and operational handovers so the platform can be maintained by the growing internal team.

• Strong hands-on platform or cloud engineering experience in production environments.

• Deep expertise in AWS or Azure, with the ability to work across a wider enterprise technology estate.

Terraform, Python or Bash, Linux, Git and Docker are particularly relevant. Kubernetes experience is useful where appropriate to the platform design.

AWS experience might include IAM, VPC, S3, ECS/EKS, KMS, Secrets Manager and CloudWatch. Azure equivalents could include Entra ID, VNets, Azure Storage, AKS, Key Vault and Azure Monitor.

Exposure to Snowflake connectivity and access management, private access to managed AI services, and monitoring tools such as Prometheus or Grafana would be valuable.

These are examples of relevant experience, not a requirement to know every product or a statement that every service is deployed.

London hybrid, with 2-3 days onsite. Inside IR35. Appointment is subject to the required security screening and clearance process.

To apply, send your CV highlighting a platform you helped build or improve, the controls it needed to satisfy and how it supported engineering teams in production.