Gen AI Architect

Gen AI Architect

Total Yrs of Experience - 10 to 15 yrs

All LTIM location

Role Overview

The AI Architect is responsible for designing and implementing advanced AI and Generative AI solutions leveraging Azure hyperscale services . This role combines deep technical expertise with strategic vision to deliver scalable, secure, and high-performance AI architectures for enterprise environments.

Key Responsibilities

• Architect and Design :
• Build end-to-end AI/GenAI architectures using Azure OpenAI , Azure AI Services , AI Foundry , and related offerings.
• Define and implement agent-based patterns leveraging frameworks like LangChain , LangGraph , CrewAI , or Autogen .
• Develop solution blueprints and technical documentation for AI systems.
• Integration and Deployment :
• Integrate AI agents and GenAI functionalities with broader IT ecosystems via APIs and secure workflows.
• Ensure compliance with enterprise requirements for security , data privacy , explainability , and scalability .
• Implement CI/CD pipelines , MLOps , and LLMOps for AI deployments.
• Collaboration and Leadership :
• Work closely with data scientists , software engineers , and business stakeholders to align AI solutions with organizational goals.
• Conduct workshops and enablement programs to drive AI adoption.
• Mentor technical teams on AI architectural best practices.

Required Skills & Qualifications

Education: Bachelors/Masters in Computer Science, Engineering, or related field.

Experience:

• 10+ years in software architecture or AI/ML, with at least 2 years in GenAI system design.
• Proven experience delivering solutions on Azure AI stack.

Technical Expertise:

• Azure Cloud & AKS architecture (GPU strategy, autoscaling, private VNet, Bastion).
• Proficiency in Python, REST API development (FastAPI/Django/Flask).
• Hands-on with LangChain, LangGraph, and prompt engineering.
• Familiarity with Azure services: Azure OpenAI, App Services, Azure Functions, ACR, Azure Files, Entra ID.
• Strong understanding of security, compliance, and explain ability in AI systems.
• Power Platform (Power Apps/Power Automate & Model Context Protocol).
• Data Layer & Pipelines: Azure SQL, Cosmos DB, PostgreSQL, Redis Cache, Dataverse, and ETL tools (ADF, Databricks).

Preferred Certifications

• Microsoft Certified: Azure Solutions Architect Expert .