We Love AI JobsAI DevOps Engineer
LingaroThis lead-level DevOps role designs and operates cloud infrastructure and deployment pipelines for enterprise AI, ML, and GenAI solutions. You would guide an AI engineering team and advise stakeholders on secure, scalable model deployments.
Skills & Expertise
Key Responsibilities
Lead architecture and deployment of AI, ML, and GenAI solutions, including LLMs and SLMs.
Automate infrastructure, model lifecycles, inference pipelines, and CI/CD for AI workloads.
Design secure cloud environments and advise stakeholders while mentoring engineers and coordinating teams.
Full Description
Seeking a Lead AI DevOps Engineer to oversee design and delivery of advanced AI/ML/GenAI solutions. The role combines cloud engineering and automation with hands-on leadership in deploying and integrating LLM/SLM models into enterprise applications, ensuring security, scalability, and operational excellence.
Tasks:
The person will act as a senior member of the Data Science & AI Competency Center, AI Engineering team, guiding delivery and coordinating workstreams.
• Leading architecture and deployment of AI/ML/GenAI solutions (LLM/SLM at scale).
• Driving automation of infrastructure, model lifecycle and inference pipelines.
• Overseeing CI/CD processes for AI/ML/GenAI workloads.
• Designing secure, scalable cloud infrastructures (Azure-focused).
• Acting as technical advisor for stakeholders and client-facing solution design.
• Mentoring engineers, promoting best practices, and fostering innovation in GenAI adoption.
• Coordinating cross-functional teams to align AI engineering with business outcomes.
• Ensuring cost optimization, monitoring and compliance across environments.
What We're Looking For:
• 5+ years in DevOps/Cloud Engineering with AI/ML/GenAI project experience.
• Proven experience deploying LLMs/SLMs (model serving, inference optimization, RAG, GenAI apps).
• Expert proficiency in Linux and macOS administration; Windows a plus.
• Advanced Python and scripting (Bash/PowerShell) for automation and integration.
• Deep knowledge of IaC (Terraform, Ansible) and CI/CD (Azure DevOps, GitHub Actions, Jenkins).
• Strong expertise in Azure cloud, Kubernetes, and enterprise AI/ML platforms.
• Track record in delivering secure, production-ready solutions for AI/ML/GenAI.
• Familiarity with monitoring, observability and FinOps practices.
• Excellent leadership, communication and mentoring skills.
• Fluency in written and spoken English.