GenAI & MLOps Engineer / Architect (Azure) 10+ Yrs experience (Only W2)
Whiz Global LLC·Washington, District of Columbia, US
Posted 2928w ago
Contractor
Apply Now About the Role
Hi ,
Hope you are doing well.
I am a resource professional with Whiz Global, IT Staffing Firm, I have below job opportunity with one of my direct clients, please advise if you are available in the job market and if yes, please go through it and send me your most recent resume and let me know when you are available to jump on a quick phone call.
Position: GenAI & MLOps Engineer / Architect (Azure)
Duration: 12 months
Location: must be local – Tuesday, Wednesday, Thursday onsite 8am-5pm
• Location: 701 9th Street NW Washington, DC 20068
Key Responsibilities
- Design and implement Azure-based GenAI applications, including RAG pipelines and agentic AI systems using foundation and multimodal LLMs.
- Build and orchestrate agentic AI and multi-agent workflows using Azure AI Agent Service, Prompt Flow, or equivalent orchestration frameworks.
- Optimize and deploy models on NVIDIA GPU hardware (e.g., A100, H100).
Required Qualifications
- 4–10+ years in ML engineering, cloud engineering, data engineering, or software engineering.
- Hands-on experience deploying LLM/GenAI applications in Azure.
- Experience implementing endtoend MLOps/LLMOps pipelines (CI/CD, model registry, monitoring, evaluation).
Experience implementing MLOps/LLMOps workflows end-to-end.
- Proficiency with Azure AI Foundry, Azure AI Agent Service, Azure AI Search, Prompt Flow, DevOps/Github Actions
Preferred Qualifications
-Azure certs. (AI Engineer, Solutions Architects, etc.)
Best Regards,
Satyendra Srivastava
IT Recruiter
Whiz Global LLC
Phone:
Address: 11555 Medlock Bridge Road
Suite 100, Johns Creek, GA 30097
What you'll do
- Location: 701 9th Street NW Washington, DC 20068
- Design and implement Azure-based GenAI applications, including RAG pipelines and agentic AI systems using foundation and multimodal LLMs
- Build and orchestrate agentic AI and multi-agent workflows using Azure AI Agent Service, Prompt Flow, or equivalent orchestration frameworks
- Optimize and deploy models on NVIDIA GPU hardware (e.g., A100, H100)
Requirements
- 4–10+ years in ML engineering, cloud engineering, data engineering, or software engineering
- Hands-on experience deploying LLM/GenAI applications in Azure
- Experience implementing endtoend MLOps/LLMOps pipelines (CI/CD, model registry, monitoring, evaluation)
- Experience implementing MLOps/LLMOps workflows end-to-end
- Proficiency with Azure AI Foundry, Azure AI Agent Service, Azure AI Search, Prompt Flow, DevOps/Github Actions