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Consultant AI DevOps Engineer | LLM Deployment & Azure
Location
Poland
Posted
78 days ago
Salary
PLN230.4K - PLN249.6K / year
Seniority
Mid Level
No structured requirement data.
Job Description
Consultant AI DevOps Engineer | LLM Deployment & Azure
Cross Border Talents
Role Description Join a leading data & AI consultancy delivering enterprise AI/ML/GenAI solutions, with a strong focus on analytics, forecasting, and AI transformation. This role combines hands-on engineering and a consulting mindset, focusing on deploying LLMs/SLMs in production, building scalable infrastructure, and advising stakeholders. This is not just DevOps — this is AI infrastructure, client-facing impact, and technical leadership. What You'll Do - Design and deploy AI/ML/GenAI systems at scale - Lead infrastructure and automation for: - Model lifecycle - Inference pipelines - Build secure, scalable Azure environments - Own CI/CD pipelines for AI workloads - Optimize performance, cost, and monitoring - Act as technical advisor to stakeholders and clients - Mentor engineers and contribute to best practices Tech Stack - Azure - Kubernetes - Terraform - Ansible - Python - Bash / PowerShell - CI/CD (Azure DevOps, GitHub Actions, Jenkins) - Linux - macOS Qualifications - 5+ years in DevOps / Cloud Engineering - Proven experience with AI/ML/GenAI systems - Deploying LLMs/SLMs in production - Strong Azure expertise (key requirement) - Advanced scripting (Python + Bash/PowerShell) - Deep knowledge of: - IaC (Terraform / Ansible) - CI/CD pipelines - Experience with Kubernetes & scalable systems Bonus - Consulting / client-facing experience - Mentoring / leadership exposure - Multi-cloud experience (AWS / GCP) - Azure certifications Compensation & Benefits - PLN 230,400 – 249,600 annually - 110+ trainings + Udemy access - Strong internal growth opportunities - Workation + flexible work model - Inclusive, DEI-driven culture Location & Eligibility - Remote within Poland - Must be based in Poland - Must have valid work authorization - No visa sponsorship Ideal Candidate Profile - Has deployed LLMs/SLMs in production (not just API usage) - Strong in Azure, automation, and infrastructure design - Comfortable in client-facing environments and advisory roles - Balances hands-on engineering and communication skills
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