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.