Description

Key Responsibilities

AI/ML Solution Architecture

• Design and architect scalable, secure, and reliable enterprise AI/ML solutions.
• Lead the architecture and technical design of Generative AI, Machine Learning, and intelligent automation solutions.
• Translate business and technical requirements into scalable AI/ML architectures.
• Define architecture patterns, technology standards, integration approaches, and deployment strategies.
• Evaluate AI technologies and recommend solutions aligned with enterprise requirements.
• Ensure AI solutions meet requirements for security, scalability, performance, reliability, and maintainability.

Generative AI & Intelligent Solutions

• Design enterprise-grade Generative AI and LLM-based solutions.
• Define architectures for AI-powered applications, copilots, intelligent assistants, and automation.
• Support integration of AI capabilities with enterprise applications, data platforms, and business workflows.
• Evaluate appropriate approaches for LLM integration, prompt engineering, RAG, AI orchestration, and model deployment.
• Establish best practices for responsible and secure implementation of AI solutions.

Microsoft AI Ecosystem

• Design and implement solutions leveraging Microsoft AI technologies, including:
  • Microsoft Foundry
  • Azure AI Services
  • Azure Machine Learning
  • Microsoft Power Platform AI capabilities
  • Microsoft 365 and Copilot integration concepts
• Evaluate Microsoft AI services and determine the appropriate technology for specific business use cases.
• Architect integrations between AI services and Microsoft enterprise platforms.
• Support enterprise adoption and modernization of AI capabilities within the Microsoft ecosystem.

Technical Leadership

• Provide technical leadership and guidance to AI/ML engineering and development teams.
• Lead architecture reviews, technical discussions, and proof-of-concept initiatives.
• Establish reusable architecture patterns and development standards.
• Collaborate with engineering, data, security, product, and business teams.
• Communicate complex AI/ML architecture concepts effectively to technical and non-technical stakeholders.

Required Qualifications

• 12+ years of overall engineering experience.
• 4+ years of experience in AI/ML Solution Architecture.
• Strong hands-on experience designing and deploying enterprise-scale AI/ML solutions.
• Strong experience with Generative AI / LLM-based solutions.
• Experience designing scalable cloud-based AI architectures.
• Strong understanding of AI/ML architecture, integration, deployment, and productionization.
• Experience with Microsoft AI technologies, including:
  • Microsoft Foundry
  • Azure AI Services and/or Azure Machine Learning
  • Power Platform AI capabilities
  • Microsoft 365 / Copilot integration concepts
• Strong understanding of cloud security, scalability, reliability, and enterprise integration patterns.
• Excellent communication, technical leadership, and stakeholder management skills.

Preferred Skills

• Experience with RAG architectures and vector databases.
• Experience with LLM orchestration and AI agent frameworks.
• Experience with Azure cloud architecture and cloud-native application development.
• Experience with APIs, microservices, and enterprise application integration.
• Experience implementing AI governance, security, monitoring, and responsible AI practices.
• Strong Python or other modern programming experience

Key Skills

Education

Bachelor's degree