GenAI Solution Lead

Overview

Remote
Depends on Experience
Contract - W2

Skills

Agentic AI
GenAI
AI/ML
Automation

Job Details

Title: GenAI Solution Lead
Location: Remote

A Solution architect that plays a role as below:

  • Works with various Corp Finance teams and identify/discover the right GenAI use cases
  • Analyse and identify right technology for those use cases(Agentic AI, GenAI, AI/ML, Automation, etc)
  • Help to build business case with ROI for AT&T leadership review
  • Design and Build implementation strategy/roadmap, How to implement using various agenticAI framework such as Langraph, Google SDK etc.
  • This role will have to collaborate with a lead based out of AT&T 3400 Plano Pkwy

AI Solution Architect Role Overview

Key Responsibilities and Preferred Qualifications

Role Overview

Analyze business use cases and design detailed AI solution architectures. Collaborate with stakeholders to understand requirements, evaluate technical feasibility, and create comprehensive architecture diagrams along with actionable deliverables that guide developers in implementing AI-driven solutions effectively.

Key Responsibilities

  • Engage with business and technical teams to review and understand AI use cases and requirements.
  • Analyze use cases to identify AI/ML opportunities and technical challenges.
  • Design scalable, secure, and efficient AI solution architectures tailored to specific use cases.
  • Develop detailed architecture diagrams and documentation illustrating solution components, data flows, integrations, and deployment models.
  • Provide clear, actionable deliverables and technical guidance for developers to implement the solutions.
  • Recommend appropriate AI technologies, frameworks, and agent development kits (e.g., Google ADK, Crew AI, LangGraph, OpenAI ADK) to meet use case needs.
  • Ensure architectures incorporate Responsible AI principles, role-based access control (RBAC), and data privacy/security considerations.
  • Continuously evaluate emerging AI technologies and best practices to improve solution designs.
  • Provide technical training and support on AI architecture and solution design as needed.

Preferred Qualifications

  • Experience with financial or SOX-sensitive data environments.
  • Certifications in AI architecture or cloud technologies.
  • Experience with enterprise AI deployments and governance.
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