Senior AI/ML Engineer

Programmers.io; Mason (OH); On-site; USD 150,000 - 190,000; Full time

Job summary

Programm ers.ai is urgently seeking a senior AI/ML Architect to lead design of scalable and secure GenAI systems. You will drive end-to-end solution development from embeddings to prompt engineering, and oversee Azure-based deployments with cost control and resilience.

Responsibilities include data architecture using Cosmos DB, Redis, Blob Storage, and Iceberg; building serverless components with Functions and Container Apps; mentoring teams and reviewing designs to ensure HIPAA/GDPR compliance.

Qualifications

• Hands-on experience with Agentic Layer A2A frameworks and MCP Protocol for multi-agent orchestration.
• Strong background in vector embeddings, prompt engineering, and context engineering for GenAI applications.
• Deep understanding of Generative AI, NLP models, and Large Language Models.

Responsibilities

• Architect and design scalable, secure AI/ML systems.
• Drive end-to-end solution development including embeddings and prompt engineering.
• Oversee deployment of AI/ML workloads on Azure Cloud with cost optimization.
• Design data pipelines and storage using Azure services and Iceberg.
• Build and manage Azure Functions and Azure Container Apps for microservices.
• Define cloud-native architecture patterns for scalable, resilient systems.
• Apply healthcare domain knowledge to meet regulatory standards (HIPAA, GDPR).
• Mentor teams and conduct design and code reviews.
• Stay ahead of GenAI, LLM Trends and integrate cutting-edge approaches.

Skills

Agentic Layer & Protocols

AI/ML Engineering

GenAI & LLM Concepts

Python

Azure Cloud

Azure Cosmos DB

Azure AI Search

Cloud-Native Architecture

Healthcare Domain

Tools

Redis

Blob Storage

Iceberg

Job description

This is Dipendra Gupta from Programmers.ai as we have an urgent open role below, please check and do let me know if you are comfortable with Job description and looking for a new role or interested.

Location: Mason ,OH or Woodland Hills ,CA (Day 1 Onsite)

Contract or fulltime

Key Responsibilities

• 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.