Haystack
← Back to Jobs
Technology
TS

Sr Agentic AI/ML Engineer – GenAI & Cloud Solutions

Tanisha Systems, Inc.Mason, OH🇺🇸United StatesPosted 10 Aug 2026

Quick Overview

Seniority
Mid Senior
Work mode
On Site
Location
Mason, OH, United States
Posted
3 weeks ago
MicroservicesAzureGDPRGenerative AIHIPAAJavaLLMPythonRedis

Job Description

Sr Agentic AI/ML Engineer – GenAI & Cloud Solutions
Location: Woodland Hills, CA / Mason OH (onsite Role)
Salary : Market - based on exp.
FTE/Full time
Start: Immediate

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.
Evaluation Criteria (Critical Components)
1. Technical Depth
  • Ability to design and implement multi-agent AI systems.
  • Experience in LLM fine-tuning, embeddings, and context engineering.
  • Expertise in coding proficiency with production-grade systems in Python.
2. Architectural Vision
  • Ability to define enterprise-level AI/ML architecture aligned with cloud-native principles.
  • Experience in scalability, resilience, and performance optimization.
3. Cloud & Data Expertise
  • Hands-on deployment of AI workloads on Azure Cloud.
  • Strong knowledge of databases, search systems, and distributed storage.
4. Domain Knowledge
  • Familiarity with healthcare regulations and ability to design compliant solutions.
5. Leadership & Collaboration
  • Experience mentoring engineers, conducting reviews, and driving technical excellence.
  • Ability to collaborate with cross-functional teams including product, compliance, and operations.
6. Innovation & Research Orientation
  • Evidence of staying current with GenAI advancements and applying them to real-world problems.
Preferred Qualifications
  • Bachelors or master’s in computer science, AI/ML, or related field.
  • Certifications in Azure Solutions Architect or AI Engineering.
  • Publications, patents, or contributions to open-source AI/ML projects.

Similar jobs

Browse related jobs

Apply now