AI/ML Engg, Lilly USA Commercial Technology

Architecture & Governance

• Define enterprise AI blueprints, platform standards, and governance frameworks for LillyUSA Commercial Technology.
• Establish engineering guardrails covering model explainability, bias mitigation, audit trails, and responsible AI compliance.
• Evaluate and onboard AI/ML tooling aligned to Lilly's approved stack: AWS, Azure, Databricks, CATS, EDB, and AWB.

Frontier AI & Applied Research

• Lead applied development in multi-agent systems, autonomous orchestration, and LLM-based solutions for commercial use cases.
• Design and deploy RAG architectures, fine-tuned models, and embedding-based retrieval systems at enterprise scale.
• Assess emerging AI research and translate relevant advances into Lilly-applicable innovations.

MLOps & Production Engineering

• Architect end-to-end MLOps pipelines: feature engineering, training, evaluation, deployment, monitoring, and retraining.
• Set CI/CD standards for ML across CATS, EDB, AWB, Azure, and AWS with automated quality gates and model governance checks.
• Ensure production-grade reliability, observability, and regulatory compliance across all deployed AI/ML systems.

AI Capability Delivery

• Translate commercial business needs into AI/ML solutions across use cases such as sales forecasting, HCP engagement, customer segmentation, and anomaly detection.
• Partner with analytics, data engineering, and product teams to embed AI capabilities into commercial workflows.

Stakeholder Engagement

• Actively promote ideas and drive decisions across multiple teams and capabilities.
• Communicate AI/ML trade-offs and recommendations clearly to both technical peers and senior business leadership.
• Represent the team in enterprise AI forums and governance bodies.

Mentorship & Team Growth

• Coach lower-level engineers in specialized AI/ML technologies to accelerate their technical growth.
• Lead design reviews and architecture discussions; contribute to internal playbooks and reusable AI frameworks.

What Success Looks Like in This Role

Delivery & Impact

Designs: Breaks down moderately complex problems and drives initiatives and solutions for increased business impact.

Knowledge Sharing

Coaches: Shares knowledge in specialized technologies to increase team members' technical growth.

Continuous Improvement

Challenges: Challenges the status quo and provides recommendations to improve processes and drive innovation.

Influence

Multiple Teams: Actively promotes ideas and impacts decisions across multiple teams and capabilities.