AI Solutions Architect

Join LTM's Business AI Practice , where we help global enterprises accelerate their AI transformation journey from experimentation to secure, production-ready deployments. We are looking for a highly experienced Azure AI Solutions Architect to lead the design, architecture, and implementation of next-generation Generative AI and Agentic AI solutions on Microsoft Azure.

This is a strategic and hands-on leadership role requiring deep expertise in Azure AI services, large language models (LLMs), intelligent agents, and enterprise-scale AI architecture. You will work closely with business leaders, customers, and engineering teams to build scalable AI solutions that deliver measurable business outcomes.

What You'll Do

• Architect and deliver enterprise-scale Generative AI and Agentic AI solutions on Microsoft Azure.
• Design and build intelligent AI agents using Azure AI Semantic Kernel , vector memory, and orchestration frameworks.
• Develop scalable AI architectures leveraging Azure OpenAI , Retrieval-Augmented Generation (RAG), and LLM-based workflows.
• Lead customer workshops, define AI adoption strategies, and create multi-year AI transformation roadmaps.
• Design secure, governed, and production-ready AI platforms aligned with enterprise standards.
• Establish best practices for AI engineering, MLOps/LLMOps, monitoring, and lifecycle management.
• Provide technical leadership, mentoring, and architectural guidance to cross-functional delivery teams.
• Remain hands-on with coding, solution development, and technical problem-solving.

Required Skills & Experience

• 10+ years of overall IT experience.
• Minimum 5+ years of experience designing and delivering solutions on Microsoft Azure.
• Strong hands-on expertise in Python for AI application development and LLM orchestration.
• Experience with:
• Azure OpenAI Service
• Azure AI Services
• Azure AI Search / Cognitive Search
• Vector Databases
• Semantic Kernel
• RAG Architectures
• LLM Orchestration Frameworks
• Solid understanding of:
• Agentic AI & Multi-Agent Systems
• MLOps / LLMOps
• CI/CD Pipelines
• AI Governance & Responsible AI
• Experience with containerized and distributed environments using:
• Kubernetes
• Docker
• Git/GitHub

Preferred Qualifications

• Microsoft Certifications such as:
• AI-102: Azure AI Engineer Associate
• AZ-204: Azure Developer Associate
• Azure Solutions Architect Expert
• Experience with large-scale data engineering and analytics platforms:
• Azure Databricks
• PySpark
• Big Data Processing Frameworks
• Exposure to enterprise AI transformation programs and stakeholder management.