AI Gateway Engineer, Data Mesh and AI Platforms team

Group Technology is modernizing its technology and data estate and accelerating adoption of AI-enabled capabilities. The role will help design, build, and operate an enterprise AI Gateway, extending API platforms to support LLM, MCP, and A2A patterns with reliable, reusable, production-ready automation.

About our team

The Data Mesh and AI Platforms team, within the Integration and AI unit, provides integration platforms including Kong and Kafka and is extending this platform approach to an AI Gateway covering LLMs, MCP, and A2A. The team engineers gateway capabilities, infrastructure automation, and reusable patterns for secure and consistent AI-service consumption in a regulated banking environment.

The team works closely with architects, cybersecurity, data governance, risk and compliance, cloud platform teams, and consuming engineering teams to ensure solutions are pragmatic, compliant, and production-ready.

The position has a hybrid working arrangement, with up to 40% remote work possible; full remote work is not available. Hiring is expected in Gdańsk or Gdynia, Poland; Copenhagen, Denmark; or Helsinki, Finland.

Main responsibilities

• Design, build, and operate AI Gateway capabilities using strong API platform and gateway engineering practices.
• Implement secure, reusable gateway patterns for LLM access, MCP servers, and A2A agent-to-agent integrations.
• Develop and maintain infrastructure as code using Terraform and support automated provisioning of gateway components.
• Build and improve CI/CD pipelines, source-control workflows, and release practices for gateway configuration and platform changes.
• Set up and automate gateway policies to expose AI capabilities consistently, with governance and developer-friendly use.
• Create and extend Kong plugins using Lua and Python for custom gateway capabilities and integrations.
• Integrate the AI Gateway with enterprise identity providers and support authentication, authorization, and access-control patterns.
• Set up logging, monitoring, and alerting for gateway services, including observability dashboards and operational insights using Splunk, Prometheus, and Grafana.
• Establish FinOps capabilities for AI Gateway usage, including cost visibility, consumption tracking, and cost-control mechanisms.
• Support onboarding of new use cases and contribute to platform documentation, reusable templates, and engineering standards.

Profile

• Strong hands-on experience designing, configuring, and operating API platforms and gateways in enterprise environments.
• Knowledge of Terraform, CI/CD, source control, IdP integration, monitoring, alerting, and automated deployment patterns.
• Knowledge of, or motivation to develop knowledge of, LLM access patterns, MCP, A2A, and securing and governing these through gateway capabilities across cloud-native AI stacks.

Education and experience

• BSc or MSc in Computer Science, Engineering, Business Informatics, or a related discipline, or equivalent practical experience.
• Professional experience as a Platform Engineer, API Gateway Engineer, DevOps Engineer, Platform Architect, or in a similar hands-on engineering role.

Required qualifications

• Strong hands-on experience with API platforms and gateway technologies in enterprise environments.
• Experience with Kong, IBM API Connect/DataPower, cloud-native gateways, or similar API-management technologies.
• Solid knowledge of Terraform and infrastructure-as-code practices.
• Experience with Kubernetes and Helm charts for deploying and managing platform or gateway components.
• Solid knowledge of CI/CD pipelines, source-control workflows, and automated release practices.
• Solid knowledge of Python and Lua for creating, extending, and maintaining Kong plugins.
• Solid knowledge of IdP integration, authentication, authorization, and access-control patterns for gateways.
• Experience setting up logging, monitoring, and alerting, including Splunk, Prometheus, and Grafana.
• Understanding of FinOps practices, including cost visibility, consumption tracking, and guardrails for platform usage.
• Experience with OpenAPI specifications, API contracts, gateway policies, and developer-facing platform documentation.
• Ability to work closely with architecture, security, risk, compliance, and engineering teams in a regulated environment.

Preferred qualifications

• Experience with Kong API/AI Gateway.
• Experience deploying gateways to AWS, Azure, or GCP.
• Familiarity with AWS, GCP, or Azure and cloud-native AI services such as Bedrock, AWS Agent Core, Google Gemini AI, or Azure AI Foundry.

Application deadline: 30/09/2026.