Senior AI/ML Engineer GenAI & Cloud Solutions
Robotics Technologies LLC
Los Angeles, CA, United States
4 days ago
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Role details
Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Compensation
$158,080.0
Working hours
Regular working hours
Job source
Tech stack
Java (Programming Language)
Artificial Intelligence
Microsoft Azure
Cloud Computing
Cloud Engineering
Code Review
Computer Programming
Databases
Data Architecture
Data Infrastructure
Distributed Systems
Python (Programming Language)
+21 more
Machine Learning
Language Modeling
Performance Tuning
Redis
Cloud Services
Software Engineering
Enterprise Search
Large Language Models
Multi-Agent Systems
Prompt Engineering
Vector Embeddings
Generative AI
Agentic-AI
Containerization
Cosmos DB
Machine Learning Operations
Data Pipelines
Serverless Computing
Container Apps
Microservices
Agent2Agent Protocol
Job description
- Architect and Design: Lead the design of scalable, secure, and high-performance AI/ML systems leveraging Agentic Layer A2A frameworks and MCP Protocols.
- Solution Engineering: Drive end-to-end solution development including vector embeddings, prompt engineering, and context engineering for enterprise-grade GenAI applications.
- Cloud Deployment: Architect and oversee deployment of AI/ML workloads on Azure Cloud, ensuring compliance, scalability, and cost optimization.
- Data Architecture: Design and optimize data pipelines and storage solutions using Azure AI Search, Redis, Cosmos DB, Blob Storage, and Iceberg.
- Application Development: Build and manage Azure Functions and Azure Container Apps for microservices-based AI solutions.
- Performance & Scalability: Define cloud-native architecture patterns, implement performance tuning, and ensure resilience across distributed systems.
- Domain Expertise: Apply deep knowledge of healthcare domain requirements, ensuring solutions meet regulatory standards (HIPAA, GDPR, etc.) and handle sensitive data securely.
- Technical Leadership: Mentor engineering teams, establish best practices, and conduct design/code reviews.
- Innovation & Research: Stay ahead of emerging GenAI, LLM/NLM trends, and integrate cutting-edge approaches into enterprise solutions.
Requirements
- Agentic Layer & Protocols: Hands-on expertise with Agentic Layer A2A frameworks and MCP Protocol for multi-agent orchestration.
- AI/ML Engineering: Strong background in vector embeddings, prompt engineering, context engineering, and fine-tuning LLMs.
- GenAI & LLM Concepts: Deep understanding of Generative AI, Natural Language Models (NLM), and Large Language Models (LLM).
- Programming: Advanced proficiency in Python; exposure to Java/Go is a plus.
- Cloud Proficiency: Strong experience with Azure Cloud services, including deployment, monitoring, and scaling.
- Databases: Expertise in Azure AI Search, Redis, Cosmos DB; familiarity with Blob Storage and Iceberg is advantageous.
- Cloud-Native Architecture: Solid grasp of microservices, containerization, serverless computing, scalability, and performance optimization.
- Healthcare Domain: Experience working with regulated data environments and compliance frameworks.
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