Job Description
The AI Lead is responsible for end to end AI solution architecture and technical leadership across complex client engagements. This role drives scalable, secure, and enterprise grade AI implementations, mentors delivery teams, and ensures high quality outcomes aligned with GT standards, Responsible AI principles, and business objectives.
Key Responsibilities
Own AI solution architecture, technical design, and implementation strategy
Lead AI delivery across multiple workstreams and teams
Define and enforce standards for AI, GenAI, data, and integration patterns
Design scalable RAG, agent based, and orchestration architectures
Guide teams on AI governance, security, privacy, and Responsible AI
Lead client architecture discussions, technical workshops, and executive demos
Review solution designs, code patterns, and delivery artifacts
Mentor and coach consultants, senior consultants, and associates
Core Tools & Technologies
Microsoft Ecosystem
Azure AI Foundry / Azure AI Studio
Azure OpenAI
Advanced prompt engineering
RAG, agent orchestration, evaluation frameworks
Copilot Studio (Premium)
Enterprise copilots, plugins, Direct Line, voice capabilities
Azure AI Search
Azure Integration Services
Azure Functions, Logic Apps
Service Bus, Event Grid
Power Platform
Enterprise grade Power Apps, Dataverse, advanced automation
CI/CD pipelines using Azure DevOps
AWS & Google Cloud
AWS AI / GenAI
Amazon Bedrock (LLM orchestration, multi model strategies)
AWS Lambda, event driven architectures
S3 and data integration patterns
Google Cloud AI
Vertex AI (GenAI workflows, model integration)
BigQuery (analytics and AI driven insights)
GenAI / LLM Platforms
Anthropic Claude
Advanced reasoning, summarization, and enterprise GenAI use cases
Experience designing multi LLM and vendor agnostic AI architectures
Programming & Engineering
Python (solution frameworks, orchestration, tooling)
REST APIs, integration design
Secure enterprise integration patterns
Skills Required
Strong architecture and solution design skills
Proven technical leadership and mentoring capability
Deep understanding of enterprise AI and GenAI patterns
Stakeholder management, risk identification, and mitigation
Ability to translate business strategy into scalable AI platforms
Required Certifications:
Microsoft Certified: Azure AI Engineer Associate (AI 102)
Or
AWS Certified Machine Learning Specialty
Or
Google Professional Machine Learning Engineer