Senior AI DevOps Engineer
Job Summary
Remote Poland
PLN/ year ( PLNmonthly)
AI MLOps Azure GenAI
Snapshot
Join a leading data & AI consultancy delivering enterprise-grade AI/ML/GenAI solutions across industries with a strong focus on forecasting analytics and AI transformation.
This role sits at the intersection of AI engineering DevOps leading the deployment and scaling of LLMs/SLMs in production environments.
This is not generic DevOps this is AI infrastructure at scale with real business impact.
Ideal Candidate Profile
- Has deployed LLMs/SLMs in real production environments (not just APIs)
- Thinks in systems automation and scalability
- Strong balance of:
- Cloud engineering
- AI system deployment
- Comfortable mentoring and working cross-functionally
What Youll Do
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Architect and deploy AI/ML/GenAI systems at scale (LLMs/SLMs)
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Build and automate:
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Infrastructure (IaC)
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Model lifecycle pipelines
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Inference workflows
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Design secure scalable cloud environments (Azure)
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Own CI/CD pipelines for AI workloads
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Optimize cost performance and monitoring
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Act as technical advisor to stakeholders and teams
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Mentor engineers and drive engineering standards
Tech Stack
- Azure Kubernetes
- Terraform Ansible
- Python Bash / PowerShell
- CI/CD (Azure DevOps GitHub Actions Jenkins)
- Linux macOS
What Were Looking For
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5 years in DevOps / Cloud Engineering
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Proven experience with:
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AI/ML/GenAI projects
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Deploying LLMs/SLMs in production
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Strong Azure expertise (non-negotiable)
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Advanced scripting (Python Bash/PowerShell)
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Deep knowledge of:
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IaC (Terraform / Ansible)
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CI/CD pipelines
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Experience with Kubernetes & scalable systems
Bonus:
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Azure certifications
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Client-facing / advisory experience
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Mentoring or leadership experience
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Cost optimization in AI workloads
Compensation & Benefits
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PLNannually
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Access to 110 trainings & Udemy
- Career growth with internal promotions (76% managers promoted internally)
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Workation policy flexible work model
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Inclusive diverse and collaborative culture
Location & Eligibility
Remote within Poland
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Must be based in Poland
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Must have valid work authorization
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No visa sponsorship
Why This Role
- Work on end-to-end AI/ML/GenAI systems (not isolated pipelines)
- Lead deployment of LLMs/SLMs in production environments
- Combine cloud architecture automation AI engineering
- Mentor engineers and shape best practices in AI DevOps
- Join a stable yet innovation-driven environment with strong learning culture
If youre ready to move beyond traditional DevOps and build AI systems that scale securely in production this is your opportunity to lead that transformation. Apply now...