Senior AI Lead / Architect

American IT SystemsOrlando, FL
Onsite

About The Position

We are seeking a highly experienced AI Lead / Architect to support evolving AI initiatives. This role will work closely with Product, Engineering, and Data teams to define, shape, and deliver practical AI-driven solutions across the organization. This is a hands-on leadership role, requiring both strategic oversight and the ability to contribute directly to solution design and implementation.

Requirements

  • 10–15+ years of experience in software engineering, data engineering, or related technical roles
  • 5+ years of experience working with AI/ML systems, including recent exposure to GenAI/LLMs
  • Proven experience designing and implementing AI-driven solutions in enterprise environments
  • Strong understanding of: LLMs and GenAI ecosystems
  • Strong understanding of: Model integration and APIs (e.g., OpenAI, Azure OpenAI, etc.)
  • Strong understanding of: Data pipelines and data architecture
  • Experience working cross-functionally with Product and Engineering teams
  • Ability to balance strategic thinking with hands-on execution

Nice To Haves

  • Experience working in regulated or data-sensitive environments
  • Familiarity with tools/platforms such as Azure AI, Databricks, or similar ecosystems
  • Prior experience helping organizations adopt AI in a structured, scalable way
  • Strong communication skills and ability to influence senior stakeholders

Responsibilities

  • Partner with Product and Engineering leadership to identify and prioritize high-impact AI/GenAI use cases
  • Define solution architectures for AI-driven capabilities across data, applications, and workflows
  • Provide hands-on technical leadership (~30–40%) in areas such as prototyping, model integration, and solution validation
  • Guide teams on best practices for leveraging AI/GenAI tools within existing development workflows
  • Support the development of scalable, reusable AI patterns and accelerators
  • Collaborate with data teams to ensure strong alignment on data readiness, governance, and model performance
  • Help establish practical frameworks for evaluating and deploying AI use cases in a controlled and scalable manner
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