{"schemaVersion":"jobsearcher.job.v1","id":"def2f8fdd2fc3cb809759fa5","url":"https://jobsearcher.com/jobs/def2f8fdd2fc3cb809759fa5","canonicalUrl":"https://jobsearcher.com/jobs/def2f8fdd2fc3cb809759fa5","title":"Senior AI/ML Engineer","description":"Senior AI/ML Engineer – GenAI & Cloud SolutionsLocation: Mason, OH (onsite Role) Duration: 6+ months Mode of interview: 2 videos\r\nKey ResponsibilitiesArchitect and Design: Lead the design of scalable, secure, and high-performance AI/ML systems leveraging Agentic Layer A2A frameworks and MCP Protocols.\r\nSolution Engineering: Drive end-to-end solution development including vector embeddings, prompt engineering, and context engineering for enterprise-grade GenAI applications.\r\nCloud Deployment: Architect and oversee deployment of AI/ML workloads on Azure Cloud, ensuring compliance, scalability, and cost optimization.\r\nData Architecture: Design and optimize data pipelines and storage solutions using Azure AI Search, Redis, Cosmos DB, Blob Storage, and Iceberg.\r\nApplication Development: Build and manage Azure Functions and Azure Container Apps for microservices-based AI solutions.\r\nPerformance & Scalability: Define cloud-native architecture patterns, implement performance tuning, and ensure resilience across distributed systems.\r\nDomain Expertise: Apply deep knowledge of healthcare domain requirements, ensuring solutions meet regulatory standards (HIPAA, GDPR, etc.) and handle sensitive data securely.\r\nTechnical Leadership: Mentor engineering teams, establish best practices, and conduct design/code reviews.\r\nInnovation & Research: Stay ahead of emerging GenAI, LLM/NLM trends, and integrate cutting-edge approaches into enterprise solutions.\r\nRequired Skills & ExpertiseAgentic Layer & Protocols: Hands-on expertise with Agentic Layer A2A frameworks and MCP Protocol for multi-agent orchestration.\r\nAI/ML Engineering: Strong background in vector embeddings, prompt engineering, context engineering, and fine-tuning LLMs.\r\nGenAI & LLM Concepts: Deep understanding of Generative AI, Natural Language Models (NLM), and Large Language Models (LLM).\r\nProgramming: Advanced proficiency in Python; exposure to Java/Go is a plus.\r\nCloud Proficiency: Strong experience with Azure Cloud services, including deployment, monitoring, and scaling.\r\nDatabases: Expertise in Azure AI Search, Redis, Cosmos DB; familiarity with Blob Storage and Iceberg is advantageous.\r\nCloud-Native Architecture: Solid grasp of microservices, containerization, serverless computing, scalability, and performance optimization.\r\nHealthcare Domain: Experience working with regulated data environments and compliance frameworks.\r\nEvaluation Criteria (Critical Components)1. Technical Depth\r\nAbility to design and implement multi-agent AI systems.\r\nExperience in LLM fine-tuning, embeddings, and context engineering.\r\nExpertise in coding proficiency with production-grade systems in Python.\r\n2. Architectural Vision\r\nAbility to define enterprise-level AI/ML architecture aligned with cloud-native principles.\r\nExperience in scalability, resilience, and performance optimization.\r\n3. Cloud & Data Expertise\r\nHands-on deployment of AI workloads on Azure Cloud.\r\nStrong knowledge of databases, search systems, and distributed storage.\r\n4. Domain Knowledge\r\nFamiliarity with healthcare regulations and ability to design compliant solutions.\r\n5. Leadership & Collaboration\r\nExperience mentoring engineers, conducting reviews, and driving technical excellence.\r\nAbility to collaborate with cross-functional teams including product, compliance, and operations.\r\n6. Innovation & Research Orientation\r\nEvidence of staying current with GenAI advancements and applying them to real-world problems.\r\nPreferred QualificationsBachelors or master's in computer science, AI/ML, or related field.\r\nCertifications in Azure Solutions Architect or AI Engineering.\r\nPublications, patents, or contributions to open-source AI/ML projects.","company":"Echo It Solutions","rawCompany":"echo it solutions","city":"Mason","state":"OH","isRemote":false,"isActive":false,"createdAt":"2026-08-08T01:24:18.854Z","occupations":[{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1243.00","title":"Database Architects","slug":"database-architects"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Senior AI/ML Engineer","description":"Senior AI/ML Engineer – GenAI & Cloud SolutionsLocation: Mason, OH (onsite Role) Duration: 6+ months Mode of interview: 2 videos\r\nKey ResponsibilitiesArchitect and Design: Lead the design of scalable, secure, and high-performance AI/ML systems leveraging Agentic Layer A2A frameworks and MCP Protocols.\r\nSolution Engineering: Drive end-to-end solution development including vector embeddings, prompt engineering, and context engineering for enterprise-grade GenAI applications.\r\nCloud Deployment: Architect and oversee deployment of AI/ML workloads on Azure Cloud, ensuring compliance, scalability, and cost optimization.\r\nData Architecture: Design and optimize data pipelines and storage solutions using Azure AI Search, Redis, Cosmos DB, Blob Storage, and Iceberg.\r\nApplication Development: Build and manage Azure Functions and Azure Container Apps for microservices-based AI solutions.\r\nPerformance & Scalability: Define cloud-native architecture patterns, implement performance tuning, and ensure resilience across distributed systems.\r\nDomain Expertise: Apply deep knowledge of healthcare domain requirements, ensuring solutions meet regulatory standards (HIPAA, GDPR, etc.) and handle sensitive data securely.\r\nTechnical Leadership: Mentor engineering teams, establish best practices, and conduct design/code reviews.\r\nInnovation & Research: Stay ahead of emerging GenAI, LLM/NLM trends, and integrate cutting-edge approaches into enterprise solutions.\r\nRequired Skills & ExpertiseAgentic Layer & Protocols: Hands-on expertise with Agentic Layer A2A frameworks and MCP Protocol for multi-agent orchestration.\r\nAI/ML Engineering: Strong background in vector embeddings, prompt engineering, context engineering, and fine-tuning LLMs.\r\nGenAI & LLM Concepts: Deep understanding of Generative AI, Natural Language Models (NLM), and Large Language Models (LLM).\r\nProgramming: Advanced proficiency in Python; exposure to Java/Go is a plus.\r\nCloud Proficiency: Strong experience with Azure Cloud services, including deployment, monitoring, and scaling.\r\nDatabases: Expertise in Azure AI Search, Redis, Cosmos DB; familiarity with Blob Storage and Iceberg is advantageous.\r\nCloud-Native Architecture: Solid grasp of microservices, containerization, serverless computing, scalability, and performance optimization.\r\nHealthcare Domain: Experience working with regulated data environments and compliance frameworks.\r\nEvaluation Criteria (Critical Components)1. Technical Depth\r\nAbility to design and implement multi-agent AI systems.\r\nExperience in LLM fine-tuning, embeddings, and context engineering.\r\nExpertise in coding proficiency with production-grade systems in Python.\r\n2. Architectural Vision\r\nAbility to define enterprise-level AI/ML architecture aligned with cloud-native principles.\r\nExperience in scalability, resilience, and performance optimization.\r\n3. Cloud & Data Expertise\r\nHands-on deployment of AI workloads on Azure Cloud.\r\nStrong knowledge of databases, search systems, and distributed storage.\r\n4. Domain Knowledge\r\nFamiliarity with healthcare regulations and ability to design compliant solutions.\r\n5. Leadership & Collaboration\r\nExperience mentoring engineers, conducting reviews, and driving technical excellence.\r\nAbility to collaborate with cross-functional teams including product, compliance, and operations.\r\n6. Innovation & Research Orientation\r\nEvidence of staying current with GenAI advancements and applying them to real-world problems.\r\nPreferred QualificationsBachelors or master's in computer science, AI/ML, or related field.\r\nCertifications in Azure Solutions Architect or AI Engineering.\r\nPublications, patents, or contributions to open-source AI/ML projects.","datePosted":"2026-08-08T01:24:18.854Z","dateModified":"2026-08-08T01:24:18.854Z","hiringOrganization":{"@type":"Organization","name":"Echo It Solutions","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Mason","addressRegion":"OH","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"def2f8fdd2fc3cb809759fa5"},"url":"https://jobsearcher.com/jobs/def2f8fdd2fc3cb809759fa5"}}