GenAI & Cloud Architect – Azure, Healthcare AI

Robotics Technologies LLC; Los Angeles (CA); On-site; USD 86,000 - 123,000; Full time

Job summary

Robotics Technologies LLC in Woodland Hills, CA seeks a Senior AI/ML Engineer GenAI & Cloud Solutions to design scalable GenAI systems on Azure, lead architecture, vector embeddings, prompt engineering, and secure data pipelines for enterprise healthcare workloads.

You will mentor teams, drive best practices, and ensure cost optimization and regulatory compliance in a distributed cloud environment.

Qualifications

• Agentic Layer & Protocols experience with multi-agent orchestration.
• AI/ML Engineering with embeddings, prompt engineering, and context engineering.
• GenAI & LLM concepts including NLP/LLMs.
• Python programming; Java/Go exposure is a plus.
• Azure Cloud proficiency including deployment, monitoring, and scaling.
• Experience with Azure AI Search, Redis, Cosmos DB; Blob Storage and Iceberg familiarity.
• Cloud-native architecture, microservices, serverless, scalability, performance optimization.
• Healthcare data handling with regulatory compliance knowledge.

Responsibilities

• Architect and design scalable, secure AI/ML systems on Azure.
• Lead end-to-end solution development for GenAI applications.
• Oversee deployment of AI/ML workloads on Azure.
• Design data pipelines using Azure storage/search services.
• Build and manage Azure Functions and Container Apps for microservices.
• Mentor teams, conduct design/code reviews and promote best practices.
• Stay ahead of GenAI trends and apply innovations to enterprise solutions.

Skills

Agentic Layer & Protocols

AI/ML Engineering

GenAI & LLM Concepts

Programming

Cloud Proficiency

Databases

Cloud-Native Architecture

Healthcare Domain

Tools

Azure Functions

Azure Container Apps

Redis

Cosmos DB

Blob Storage

Iceberg

Job description

Robotics Technologies LLC in Woodland Hills, CA seeks a Senior AI/ML Engineer GenAI & Cloud Solutions to design scalable GenAI systems on Azure, lead architecture, vector embeddings, prompt engineering, and secure data pipelines for enterprise healthcare workloads.

You will mentor teams, drive best practices, and ensure cost optimization and regulatory compliance in a distributed cloud environment.