Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 3
API @ 3
Agentic AI
BI
CI/CD @ 3
Compliance
DevOps @ 5
Distributed Systems @ 3
Docker @ 3
GCP @ 3
GenAI
Generative AI
Go
IaC
Kubernetes @ 3
Machine Learning
Microservices @ 3
Observability @ 3
Security
Terraform @ 3
Vertex AI @ 3
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
ING Hubs Poland is building VISTA, a shared, production-grade Data and AI platform on Google Cloud. The platform supports Analytics, Business Intelligence, Machine Learning, Generative AI, and Agentic AI solutions at scale, with governance, security, compliance, and self-service capabilities embedded by design.
As a GCP Cloud AI Platform Engineer, you will help build and evolve the cloud foundations, automation tooling, and self-service platform experiences that enable AI Engineers, Data Scientists, Data Engineers, and analytics teams to build, deploy, and operate production-grade AI solutions.
Responsibilities
- Build and maintain components of ING's Data, Analytics, and AI Platform on Google Cloud.
- Develop Golang-based infrastructure automation services and platform tooling.
- Prepare cloud-ready and Infrastructure as Code-based solutions using Terraform and CI/CD pipelines.
- Support platform tenants and help them onboard smoothly.
- Maintain and improve key platform components.
- Contribute to platform architecture, standards, and engineering practices.
- Implement and improve monitoring, logging, and alerting for platform services.
- Support operational stability, including participation in on-call support where applicable.
- Collaborate with stakeholders, data engineers, data scientists, and platform users to deliver scalable, secure, and cost-efficient cloud solutions.
Requirements
- At least 3 years of hands-on experience with Google Cloud Platform, preferably in platform engineering, cloud infrastructure, or DevOps-oriented roles.
- Practical experience building or maintaining platforms on GCP using managed services such as Cloud Run, GKE, BigQuery, Dataproc, Vertex AI, and Google Cloud Storage, or similar services.
- Hands-on experience with Golang is required, including concrete examples involving CLI tools, microservices, automation services, provisioning tools, APIs, integrations, or concurrency-based implementations.
- An Infrastructure as Code mindset and practical experience with Terraform.
- Experience with deployment and provisioning automation, including Docker, Kubernetes, and CI/CD pipelines.
- Hands-on experience with monitoring, logging, alerting, observability, and basic production troubleshooting.
Additional Qualifications
- Experience with secure authentication and encrypted workloads, such as OIDC, KMS, and SSL/TLS.
- Experience with distributed systems or large-scale data processing on GCP.
- Experience supporting internal platform users or tenants.
Team and Technical Environment
The team is developing ING's next-generation Value-driven Insights and Scalable Technology Analytics Platform on Google Cloud. The role combines Platform Engineering, Cloud Infrastructure, Generative AI, Agentic AI, and Intelligent Automation. The team values ownership, automation, curiosity, and a practical engineering mindset while maintaining production reliability, security, and quality.
The role naming convention in the global ING job architecture will be "Engineer IV".