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:

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5+ years in DevOps/Cloud Engineering with AI/ML/GenAI project experience.

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Proven experience deploying LLMs/SLMs (model serving, inference optimization, RAG, GenAI apps).

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Expert proficiency in Linux and macOS administration; Windows a plus.

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Advanced Python and scripting (Bash/PowerShell) for automation and integration.

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Deep knowledge of IaC (Terraform, Ansible) and CI/CD (Azure DevOps, GitHub Actions, Jenkins).

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Strong expertise in Azure cloud, Kubernetes, and enterprise AI/ML platforms.

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Track record in delivering secure, production-ready solutions for AI/ML/GenAI.

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Familiarity with monitoring, observability and FinOps practices.

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Excellent leadership, communication and mentoring skills.

- Fluency in written and spoken English.

Originally posted on Himalayas