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Senior Expert AI Engineer

70k - 100k EUR70 000 - 100 000 EUR/ rok./ rok.UoPUmowa o pracę (brutto)

SeniorZdalnie·BudapestFull-time·Umowa o pracę

#462565·Dodano 9 dni temu·3

Źródło: nofluffjobs.com

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Tech Stack / Keywords

Kubernetes AKSDocker ComposeAzureInfrastructure as CodeTerraformBicepAnsible Python GitAutomated testingAIDevOpsData engineering

Podsumowanie oferty

In the Corporate IT team, you will build the technical foundation for the internal AI platform and make AI applications operable in production. You will integrate language models with enterprise data through RAG and create the conditions for reliable operations.

Wymagania

Strong experience with Kubernetes/AKS, Docker Compose, and Azure Container Apps.
Experience with infrastructure as code using Terraform, Bicep, or Ansible.
Experience with vector databases and embedding pipelines.
Solid skills in Python, APIs, Git, and automated testing.
German at B2 level and English at B2–C1 level.

Nice to have:

Experience with Azure, Entra ID, and M365.
Experience with model serving or inference operations, for example vLLM.
Experience with enterprise AI platforms and their integration with enterprise data.
Basic understanding of DORA, BAIT/VAIT, and outsourcing requirements.
Experience in platform engineering, DevOps, or data engineering.

Obowiązki

AI platform:

Develop the internal AI platform and prepare it for productive applications, including architecture, monitoring, cost control, and operating and access models.

Production systems:

Take responsibility for the orchestration and resilience of containerized applications running in production.

API integration:

Integrate language models through production APIs and connect enterprise data through RAG.

Cost & quality:

Set up evaluation, tracing, and guardrails in the production environment to balance cost and quality.

Architecture:

Make architecture decisions when technical and business requirements compete, make trade-offs transparent, and stand behind the outcome.

Data & routing:

Take responsibility for data ownership and model routing, and consider resilience in the technical design.

Agentic systems:

Make tool calls, approvals, audit trails, idempotency, and reliable restart mechanisms work in production for agentic systems.

Software engineering:

Apply sound design, automation, and testability, using engineering and scripting skills to put these principles into practice.

From sandbox to production:

Build the sandbox and toolchain for AI Builders, take initial internal use cases through to ongoing operations, and create the foundations for a multi-tenant platform with potential future customer-facing use cases.

Benefity

Team events, including get-togethers and team-building sessions.
Flexible working hours.
Access to LinkedIn Learning.
Targeted development programs.

Spotkania integracyjne

Elastyczne godziny

Inne informacje

Occasional travel within the DACH region.

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