AI DevOps Engineer

Job 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.