Senior AI/ML Engineer

Natsoft; Mason (OH); On-site; USD 140,000 - 200,000; Full time

Job summary

Natsoft is seeking a senior Architect and Design leader to craft scalable, secure AI/ML systems using Agentic Layer A2A and MCP protocols. You will guide solution engineering for end-to-end GenAI applications and oversee Azure-based deployments.

You will shape data architectures with Cosmos DB, Redis, Blob Storage, and Iceberg; build microservices with Azure Functions and Container Apps; ensure HIPAA/GDPR compliance; mentor teams, review designs, and pioneer new GenAI approaches across

Qualifications

• Hands-on experience with Agentic Layer A2A frameworks and MCP Protocols.
• Strong background in vector embeddings, prompt and context engineering.
• Deep knowledge of Generative AI, NLMs, and LLMs.
• Proficient in Python; knowledge of Java or Go is a plus.
• Experience with Azure Cloud services including deployment and monitoring.
• Familiarity with Azure AI Search, Redis, Cosmos DB, Blob Storage, Iceberg.
• Understanding of cloud-native architectures, microservices, and serverless computing.
• Experience in regulated data environments and HIPAA/GDPR awareness.

Responsibilities

• Architect and design scalable AI/ML systems leveraging Agentic Layer A2A frameworks.
• Drive end-to-end GenAI solution development including vector embeddings and prompt engineering.
• Oversee Azure Cloud deployments ensuring scalability, cost optimization, and compliance.
• Design data pipelines using Azure Cosmos DB, Redis, Blob Storage, Azure AI Search, and Iceberg.
• Build and manage Azure Functions and Container Apps for microservices-based solutions.
• Define cloud-native patterns for performance and resilience across distributed systems.
• Apply healthcare domain knowledge to meet regulatory standards and secure sensitive data.
• Provide technical leadership through mentoring, reviews, and best-practice enforcement.
• Stay ahead of GenAI trends and integrate cutting-edge approaches into enterprise solutions.

Skills

Agentic Layer & Protocols

AI/ML Engineering

GenAI & LLM Concepts

Python Programming

Azure Cloud Proficiency

Cloud-Native Architecture

Healthcare Domain Knowledge

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.

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.