Senior / Lead DevOps Engineer – Platform Engineering | Hungary
Posted
Shape the Infrastructure Behind Enterprise AI 🚀
AI is no longer experimental — it is mission-critical. As global organizations deploy autonomous AI agents on sensitive data, they need secure, scalable, and compliant platforms that meet the same reliability standards as any enterprise production system.
This is where you come in.
🟢 We are looking for a Senior or Lead DevOps Engineer to design, build, and operate enterprise-grade Agentic AI platforms. You will be a hands-on technical leader — owning architecture and delivery while mentoring engineers and partnering closely with client and internal teams. You will help some of the world’s most recognized organizations run secure AI environments at scale under strict regulatory and security requirements.
If you are excited about deep cloud-native engineering with real consulting impact, this role offers exactly that.
💼 Your Profile
We are looking for a technically strong leader who is comfortable operating in complex environments.
Core Competences
- 4–8+ years in DevOps, Site Reliability Engineering (SRE), Cloud Engineering, or Platform Engineering
- Proven experience delivering complex projects in Azure (preferred), AWS, or GCP
- Strong hands-on expertise in Kubernetes (AKS/EKS/GKE), Helm, Kustomize, and container orchestration at scale
- Deep experience with CI/CD automation and pipeline design (GitHub Actions, Azure DevOps, GitLab CI, or Jenkins)
- Infrastructure as Code (Terraform, Bicep, or Pulumi) across Dev, Test, and Production environments
- Practical experience with observability (Azure Monitor, Datadog, Prometheus/Grafana, or OpenTelemetry)
- Strong scripting and automation skills (Python, Bash, or PowerShell)
- Strong English and native Hungarian are mandatory
Security & Compliance Mindset
- Identity & access management
- Encryption (at rest and in transit)
- Understanding of SOC2 / ISO-level compliance standards
Technical Leadership & Consulting Capabilities
- Ability to own technical workstreams end-to-end — from design through implementation and production support
- Experience defining CI/CD patterns, IaC standards, and platform reference architectures for others to follow
- Comfortable acting as incident commander or technical lead during critical production issues
- Strong collaboration with Engineering, Security, Architecture, and Data Science stakeholders
- Excellent communication in English; ability to explain technical trade-offs clearly to mixed audiences
- Experience working in agile, international, and hybrid delivery environments
Nice to Have
- Experience with LLMOps, GenAI production environments, or Agentic AI platforms
- Vector databases (Milvus, Pinecone, Azure AI Search) and RAG architecture deployment
- GPU workload scheduling and AI-specific observability (Langfuse, LangSmith, or similar)
- Workflow/orchestration platforms (n8n, Airflow, Step Functions)
- FinOps practice: cloud cost analysis, optimization, and reporting
- Platform Engineering patterns, Internal Developer Platforms (IDP), and GitOps (Argo CD, Flux)
- DevSecOps tooling: policy-as-code, SAST/DAST, SBOM, and secrets scanning in CI/CD pipelines
- Cloud or DevOps certifications (Azure, AWS, CKA, Terraform Associate)
Skills
- Agentic AI
- Agile
- AI
- Airflow
- AKS
- Automation
- AWS
- Azure
- Azure DevOps
- Bash
- Bicep
- CI/CD
- Cloud
- Cloud Native
- DAST
- Data Science
- Datadog
- DevOps
- DevSecOps
- EKS
- FinOps
- Flux
- GCP
- Generative AI
- GitHub
- GitHub Actions
- GitLab
- GitOps
- GKE
- Grafana
- Helm
- Infrastructure as Code
- Jenkins
- Kubernetes
- LangSmith
- LLMOps
- Milvus
- n8n
- Observability
- OpenTelemetry
- Pinecone
- PowerShell
- Prometheus
- Pulumi
- Python
- SAST
- SOC 2
- Terraform
- Vector Databases