Description & Requirements

Who we are looking for

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)

Your future role

🎯Your Impact

🔐 Security & Governance

Architect Zero-Trust environments for LLM-based solutions
Implement private networking (Private Link), granular RBAC (Entra ID), and automated policy enforcement
Ensure compliance with enterprise security and audit standards

🔄 LLM Lifecycle & Production Enablement

Bridge Data Science and Engineering
Implement agent observability (Langfuse / LangSmith)
Automate RAG architecture deployment
Build scalable pipelines from experimentation to production

🏗 Infrastructure as Code

Standardize environments using Terraform or Bicep
Ensure reproducible Dev, Test, and Prod environments across global deployments

📊 Observability & Transparency

Implement monitoring (Azure Monitor, Datadog)
Integrate SIEM solutions
Enable traceability and explainability of AI systems

What we offer

Join a fast-growing AI & Data Excellence team in Hungary, connected to a global network of 160+ specialists and strategic partnerships with Microsoft, Google, and AWS.

📈 Real Career Acceleration

This is not just another DevOps role. You will:

You will work on high-profile international engagements where your architecture decisions directly influence how enterprises operate with AI.
Lead complex AI platform initiatives
Influence architecture decisions at enterprise level

Benefits:

Modern Working Environment
Competitive salary + annual performance bonus
Cafeteria package & SZÉP card (accommodation, catering, recreation)
Contribution to nursery or kindergarten services
Comprehensive health coverage (Medicover health insurance & group life insurance)
Pension fund contributions
Commuting allowance
Hybrid working model
International exposure
Continuous learning & certification support

Selection process

Apply with your CV in English

Please submit an up-to-date CV in English as part of your application.

HR Screening Call

An initial conversation with our Talent Acquisition team to discuss your experience, motivation, language skills, and overall fit for the role.

Technical Interview with the Hiring Manager

A deeper discussion focused on your technical expertise, project experience, leadership capabilities, and alignment with the role requirements.

Final Meeting with the AI & Data Director

A final get-to-know-you conversation focused on your career aspirations, leadership approach, and potential contribution to Deloitte's AI & Data practice

General Information

Position

Senior / Lead DevOps Engineer – Platform Engineering | Hungary

Work arrangement

Full-time

City

Budapest

Country

Hungary

Department

Consulting

Team

Engineering, AI & Data

Area of interest

AI - Artificial Intelligence, Cloud, Data & Analytics, Digital, Engineering

Way of work

Hybrid

Senior / Lead DevOps Engineer – Platform Engineering | Hungary

About the role

Skills

Benefits

Perks

Full job details

Description & Requirements

General Information