Senior AI/ML Engineer

Quantum Technologies. LLC; Woodland (CA); On-site; USD 170,000 - 250,000; Full time

Job summary

Quantum Technologies. LLC seeks a senior AI/ML Architect to lead scalable, secure GenAI solutions on Azure. You will drive end-to-end design, embeddings, prompt and context engineering for enterprise-grade applications, with a focus on compliant data handling in healthcare environments.

The role emphasizes cloud-native architectures, performance tuning, and mentoring teams to adopt best practices in multi-agent GenAI deployments. On-site position in Woodland, CA.

Qualifications

• Experience designing scalable AI/ML architectures in cloud environments.
• Strong background in vector embeddings, prompt/context engineering for GenAI.
• Familiarity with regulated healthcare data, HIPAA/GDPR considerations.

Responsibilities

• Architect and design scalable, secure AI/ML systems using Agentic Layer A2A frameworks and MCP Protocols.
• Drive end-to-end solution development including embeddings, prompts, and context engineering for GenAI apps.
• Oversee Azure-based deployment of AI/ML workloads with emphasis on scalability, cost optimization, and compliance.
• Design data pipelines and storage using Azure AI Search, Redis, Cosmos DB, Blob Storage, and Iceberg.
• Develop and manage Azure Functions and Azure Container Apps for microservices-based AI solutions.
• Define cloud-native architecture patterns, performance tuning, and resilience for distributed systems.
• Apply healthcare domain knowledge to ensure regulatory compliance and secure data handling.
• Provide technical leadership through reviews, best-practices, and mentoring.

Skills

Agentic Layer

MCP Protocol

Vector embeddings

Prompt engineering

Context engineering

LLMs

Python

Azure Cloud

Cloud deployment

Security & compliance

Healthcare domain

Tools

Azure Functions

Azure Container Apps

Cosmos DB

Redis

Blob Storage

Iceberg

Azure AI Search

Kubernetes

Job description

US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other

Work Authorization: USC, GC, H-1B, OPT-EAD, GC-EAD, H4-EAD

Job Summary

• 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.

Required Skills & Expertise

• 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

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.