We are seeking a senior Ops Engineer to support GenAI, LLM, and ML workloads, with a strong focus on deployment automation, observability, scalability, and platform reliability across Azure and Kubernetes environments.

Key Responsibilities :

- Build and maintain CI/CD/CT pipelines for ML models, LLMs, and GenAI workloads

- Deploy and operationalize :

a. ML models and custom LLMs

b. AI agents and GenAI services using Databricks, MLflow, AKS / ARO

- Integrate and scale GenAI ecosystems including :

a. Azure OpenAI / OpenAI

b. HuggingFace models

c RAG pipelines and vector databases

- Support development and deployment of custom models and out of the box AI agents

- Manage Databricks :

a. Workspaces

b. Clusters

c. Model registry

d. Job orchestration

- Own AKS / ARO lifecycle, including networking, scaling, Helm based deployments, and GitOps workflows

- Implement robust observability for AI/ML/LLM systems (latency, drift, reliability, performance)

- Ensure cloud security, governance, access controls, and cost efficiency

Required Skills :

- Strong hands on experience with Azure, AKS/Kubernetes, Databricks, MLflow

- Experience with LLMOps, RAG pipelines, and vector stores (FAISS, Pinecone, Chroma, etc.)

- Proficiency in Python and automation scripting

- Strong understanding of AI/ML system operations and platform reliability