Description :

Location : Bangalore

Experience Required : 58 years

Tech Stack : Azure | Databricks | AKS | ARO | Kubernetes | MLflow | GitHub Actions | Python | Helm | GitOps | Vector Stores | GenAI Frameworks

Role Summary :

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 :

- ML models and custom LLMs

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

Integrate and scale GenAI ecosystems including :

- Azure OpenAI / OpenAI

- HuggingFace models

- RAG pipelines and vector databases

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

Manage Databricks :

- Workspaces

- Clusters

- Model registry

- 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