Sr. Principal Engineer AI/ML System Integration

At Lilly, the work is demanding because patients are waiting. We unite caring with discovery to help make life better for people around the world, knowing that every decision, every detail, and every day matters. Headquartered in Indianapolis, Indiana, our over 50,000 employees around the globe take on complex challenges to discover and deliver life-changing medicines, strengthen how health is understood and managed, and support the communities we serve. This is hard, urgent, selfless workbut its work worth doing. If youre driven by purpose and ready to bring your best to work that truly matters for patients, we invite you to join us.

Role Overview

We are seeking a Sr. Principal Engineer to lead the architecture and integration of AI/ML-enabled applications across enterprise platforms, data ecosystems, commercial workflows, and third-party services. This role owns the technical integration strategy that brings together business applications, APIs, data products, machine learning models, large language models, agents, security controls, and human workflows into secure, resilient, observable, and scalable solutions.

This is a senior individual contributor and cross-team technical leadership role. The successful candidate will partner with product managers, AI/ML engineers, software engineers, data teams, platform owners, enterprise architects, cybersecurity, privacy, compliance, vendors, and business stakeholders to deliver end-to-end AI-enabled capabilities

Key Responsibilities

Enterprise & AI Solution ArchitectureLead architecture and integration strategy for AI/ML-enabled products and platforms.Design scalable solutions that integrate applications, APIs, data platforms, AI services, and business workflows.Establish reusable integration patterns, architecture standards, and technical governance practices.AI Platform & Application IntegrationIntegrate AI/ML capabilities, LLMs, RAG solutions, agents, and analytics services into enterprise applications.Guide technical decisions regarding model usage, orchestration, workflow automation, and human-in-the-loop controls.Ensure solutions are secure, resilient, observable, and operationally supportable.Data, Platform, and Cloud IntegrationDesign and govern data flows across operational systems, data platforms, semantic layers, and AI services.Partner with platform and engineering teams to enable scalable cloud-native architectures and deployment models.Ensure data quality, security, lineage, and compliance requirements are addressed.Quality, Governance & Operational ExcellenceEstablish end-to-end testing, monitoring, observability, and AI evaluation practices.Promote Responsible AI principles, security-by-design, and privacy-by-design approaches.Drive production readiness, operational support models, and continuous improvement practices.Technical LeadershipServe as a trusted technical advisor to product, engineering, architecture, security, and business stakeholders.Lead architecture reviews and influence technical strategy across multiple initiatives.Mentor engineers and architects while promoting engineering excellence and knowledge sharing.Required Qualifications8+ years of experience in software engineering, solution architecture, systems integration, or platform engineering.Experience architecting and delivering complex enterprise solutions integrating multiple systems, platforms, and data sources.Strong understanding of cloud-native architecture, APIs, microservices, event-driven systems, and integration patterns.Experience with AI/ML-enabled applications, including LLMs, RAG, agentic workflows, or related technologies.Experience with cloud platforms such as Azure, AWS, or GCP.Familiarity with MLOps, LLMOps, DevSecOps, and modern software delivery practices.Strong communication, stakeholder management, and technical leadership skills.Preferred QualificationsExperience in healthcare, life sciences, commercial analytics, CRM, field engagement, or customer engagement platforms.Experience with Databricks, Azure AI, Azure OpenAI, AWS AI/ML services, or similar enterprise AI platforms.Experience with semantic search, vector databases, knowledge graphs, or agent-based architectures.Experience with enterprise architecture, technical governance, and vendor management.Key SkillsEnterprise Integration ArchitectureAI/ML & Generative AI SolutionsCloud & Platform ArchitectureAPI & Event-Driven DesignData & Knowledge IntegrationAgentic AI & Workflow OrchestrationMLOps / LLMOpsResponsible AI & GovernanceArchitecture LeadershipStakeholder & Vendor Management

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