AI & Automation Architect / AI Solutions Engineer

Location: Indianapolis, IN — Onsite
Duration: 6 months
GBaMS ReqID: 10799226

Job Title

• AI & Automation Architect / AI Solutions Engineer

Role Responsibilities

• Lead the design and implementation of AI and automation solutions across Lilly business functions, including:
  • Medical
  • Clinical
  • Commercial
• Architect and build:
  • LLM-powered applications
  • AI agents
  • Intelligent automation frameworks
• Drive end-to-end solution delivery across:
  • Requirements gathering
  • Solution design
  • Development/build
  • Testing
  • Deployment
  • Scaling
• Lead Proofs of Concept (PoCs) and pilot initiatives.
• Drive enterprise-scale rollouts of AI and automation solutions.
• Define and implement best practices for:
  • AI architecture
  • MLOps
  • Reusable AI accelerators
• Collaborate with:
  • Business stakeholders
  • Subject Matter Experts (SMEs)
  • IT teams
• Identify opportunities for business and technology transformation through AI and automation.
• Ensure solutions meet required:
  • Quality standards
  • Performance standards
  • Security standards
  • Compliance requirements
• Ensure compliance with regulated environments and standards, including:
  • GxP
  • HIPAA
• Support client-facing activities, including:
  • Client interactions
  • Solution demonstrations
  • Executive-level discussions

Essential Skills

• 4–6 years of experience with strong expertise in:
  • Artificial Intelligence
  • Automation
  • Enterprise application development
• Strong understanding of:
  • API integration
  • Microservices architecture
  • Workflow orchestration
• Experience with data processing involving:
  • Structured data
  • Unstructured data
• Hands-on experience with ETL pipelines.
• Knowledge of the Azure cloud ecosystem, preferred.
• Familiarity with Azure AI services.
• Experience designing and implementing enterprise-grade AI and automation solutions.

Technical Skills

• AI/Artificial Intelligence
• Generative AI
• Large Language Models (LLMs)
• AI Agents
• Intelligent Automation
• AI Architecture
• MLOps
• API Integration
• Microservices
• Workflow Orchestration
• ETL/Data Processing
• Azure Cloud
• Azure AI Services
• Enterprise Application Development
• Data Warehouse

Experience Required

• 4–6 years