About us
act digital is an international consulting and engineering group that supports its clients in their digital transformation projects.
Present in 12 countries and with more than 7,000 employees, we leverage our expertise to address their challenges in software development, cybersecurity, data, cloud, and AI.
Our ambition: to become the trusted technology partner of the most innovative companies, by designing and securing systems that enhance their performance and resilience.
Joining act digital means becoming part of an agile and committed organization that works closely with its clients to turn ideas into concrete results, with pragmatism and high standards.
Job description
You will join our team of experts in IT Data and Analytics Department.
Your responsibilities will include:
- Build and operate the platform's container runtime across environments (dev, acc, pro): cluster lifecycle, node provisioning and autoscaling, upgrades, storage and cost.
- Own service-to-service networking and traffic management: ingress, mutual TLS, routing, network and admission policies that enforce the platform's security and high-availability standards.
- Design and maintain the infrastructure as code that defines the platform, its automated tests, and the CI/CD pipeline that validates and applies changes per environment.
- Package and deploy platform components and controllers: the model gateway and its data stores, the isolated runtime for agent code, DNS, certificate and secrets integrations.
- Implement identity and access end to end: workload identities, federation with the corporate identity provider and with external clouds, user login and token-based access for machine clients, secrets management.
- Build and operate the controlled public entry to the platform: edge load balancing, web application firewall, DNS and certificates, and the rules that decide what is reachable from where.
- Make the platform observable: logs, metrics and alerts for the runtime, the network and the AI workloads, including model usage and cost.
- Onboard use-case teams: provide the patterns, isolation boundaries, policies and documentation they need to run agents and tool integrations (e.g. MCP-based) safely on the platform, each backed by a documented, validated value case.
- Contribute to technical designs and architecture decisions together with the tech lead and architect, and keep the documentation, diagrams and decision records in step with the implementation.
- Embed security, responsible AI guardrails, governance and compliance by design (including AI Act considerations), in collaboration with architecture and data governance.
- Monitor platform performance, reliability and cost, and contribute to ongoing optimisation.
Required qualifications
What profile are we looking for this position:
Must-have skills :
- Operating a container platform in production (Kubernetes or equivalent): workloads, networking, access control, upgrades, troubleshooting.
- Service mesh and traffic management concepts: gateways, mutual TLS, routing, authorization policies.
- Infrastructure as code (Terraform or equivalent): reusable modules, state across environments, automated testing.
- Container fundamentals and packaging (Docker, Helm or equivalent, image registries).
- Cloud platforms, AWS strongly preferred: networking, IAM, load balancing, WAF, DNS, certificates, key and secrets management.
- Security and identity: OIDC and SAML federation, workload identity, secrets management, secure-by-design integration patterns.
- CI/CD with Git (GitLab or similar), working through merge requests and code review.
- Observability: metrics, logs, tracing and alerting with a cloud-native or vendor stack.
- Scripting in Python or Bash for tooling and automated checks.
- Strong analytical and problem-solving abilities. Strong documentation and communication skills; comfortable writing architecture decision records.
- Fluent in English (verbal and in writing), Dutch or French optional.
Nice to have :
- Running model gateways or model access components (e.g. LiteLLM, AWS Bedrock, Azure OpenAI).
- Sandboxing and workload isolation (e.g. gVisor, Kata Containers, seccomp).
- Agentic AI concepts and tool integrations (e.g. MCP), seen from the hosting side.
- RAG, embeddings and vector stores; data platforms and warehouses such as Snowflake.
- Policy as code (e.g. OPA, Kyverno, Kubernetes admission policies).
- Data governance, security frameworks and AI Act / responsible AI principles.
- Working with AI coding assistants in a reviewed, test-driven workflow.
- Experience with agile methodologies and DevOps practices.