LLM Agentic AI Solution Architect

LLM Agentic AI Solution Architect

Client: WinWire
Location: Santa Clara, CA – Onsite
Employment: FTE – CONTRACT 
Experience: 12+ Years

Required Primary Skills

Candidates must clearly mention the exact years of experience for the primary skills in the resume and demonstrate these skills across relevant projects:

• Cloud AI Platforms – AWS SageMaker, Azure ML, Google Cloud Platform AI

• Azure OpenAI

• Azure AI Studio

• Kubernetes

• LLM Orchestration & LLM Architecture

• Retrieval-Augmented Generation (RAG)

• APIs & Custom Connector Integration

• Agentic AI / Multi-Agent Orchestration

• LangChain, LangGraph, A2A, MCP

Required Experience

• 6–10 years of AI/ML/Deep Learning model development

• 2–3 years hands-on experience with LLMs, NLP, or Speech/Voice AI

• 3–5 years deploying AI solutions in production

• 5+ years Python, PyTorch, TensorFlow, or similar frameworks

• 3–5 years designing, training, and fine-tuning LLM/AI models

• 5 years experience with cloud AI platforms such as AWS SageMaker, Azure ML, or Google Cloud Platform AI

• 2+ years with Agentic AI frameworks including LangChain, LangGraph, A2A, MCP, and multi-agent orchestration

• 2–3 years with model evaluation, bias detection, and optimization

• 5 years integrating AI models into applications through APIs or pipelines

• 2–3 years with Azure AI services including:

  • Azure AI Speech & Translator

  • Azure OpenAI

  • Azure AI Search

  • Azure Container Apps / AKS

  • API Management

  • Event Hubs

  • Key Vault

  • Application Insights

Education & Certifications

• Bachelor’s or Master’s degree in Computer Science, AI/ML, Data Science, or related field

• Advanced coursework or certifications in Machine Learning, Deep Learning, or NLP

• Strong mathematical and statistical foundation

Responsibilities

• Design, develop, and deploy advanced AI/LLM solutions

• Build scalable and production-ready Agentic AI architectures

• Design RAG and multi-agent solutions

• Integrate AI models with enterprise applications using APIs and custom connectors

• Evaluate, fine-tune, optimize, and monitor AI models

• Collaborate with Data Engineering, LLMOps, and Software Engineering teams

• Research emerging AI/ML technologies and recommend solutions

• Mentor junior AI engineers and review AI architecture, code, and models

• Troubleshoot AI deployment, integration, performance, and scalability challenges

Communication & Collaboration

• Clearly explain AI concepts and model behavior to technical and non-technical stakeholders

• Present complex AI/model results in a concise and actionable manner

• Work effectively with cross-functional teams

• Provide technical guidance and mentor junior engineers

• Experience working in Agile/Scrum environments

• Exposure to Jira / Azure DevOps

• Strong analytical and problem-solving skills

Important: Candidates must be able to clearly demonstrate the required technologies and exact years of experience in their resume/project descriptions.