AI DevOps Engineer

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. Originally posted on Himalayas