AI Delivery Lead

AI Delivery Lead eClinical Solutions is transforming clinical development with elluminate®, our Clinical Data Cloud , helping life sciences organizations unify, analyze, and unlock the value of their data faster than ever before. By combining a modern cloud platform with expert data services, we empower smarter decisions across the clinical trial lifecycle—accelerating innovation that ultimately improves patient outcomes. Our engineering teams build enterprise-grade, revenue-generating products at the intersection of cloud, data, analytics, and emerging AI technologies . If you’re excited about building sophisticated software that makes a real-world impact on healthcare, this is the place to do it. You will make an impact: As an AI Delivery Lead , you will help transform how eClinical Solutions Engineering teams plan, build, test, and deliver software by driving adoption of AI-enabled software development practices across the organization. You will work closely with Engineering, SQA, Product Management, Architecture, and DevOps to embed AI-assisted development and automation throughout the Software Development Lifecycle (SDLC). You will help teams identify opportunities to eliminate manual activities, improve delivery predictability, strengthen automated quality, and demonstrate measurable improvements in engineering productivity and software delivery. This role is ideal for someone who combines strong software delivery and Agile experience with a practical understanding of AI-assisted development and enjoys working directly with teams to turn new technologies and processes into repeatable engineering practices. Your day to day: • Drive adoption and continuous improvement of AI-assisted development and AI-DLC practices across Engineering teams. • Work directly with Engineering, SQA, Product, Architecture, and DevOps throughout planning, development, testing, and release. • Partner with teams during backlog refinement and sprint planning to improve story readiness, identify dependencies, and ensure development and automated testing are considered together. • Identify opportunities to use AI and automation to reduce manual activities across requirements analysis, development, testing, documentation, and delivery. • Help teams incorporate AI-assisted workflows into their day-to-day engineering practices using company-approved tools. • Drive stronger integration between software development and test automation, including API and UI automation as part of feature delivery. • Identify delivery bottlenecks, dependencies, and process gaps and work with teams to resolve them. • Establish repeatable AI-enabled delivery practices and help scale successful approaches across multiple Engineering teams. • Define and track meaningful delivery metrics, including cycle time, rework, automation coverage, manual test reduction, quality, and AI adoption. AI & Modern Engineering Focus We’re actively incorporating AI-powered capabilities into our platform, and you’ll help shape how this is done responsibly and effectively in an enterprise environment. This includes: • Integrating and building LLMs and AI services into .NET- and Python-based systems • Designing and implementing AI-assisted workflows , copilots, or intelligent automation features • Working with agentic AI patterns (e.g., task orchestration, tool-using agents, workflow automation) • Applying prompt engineering, evaluation techniques, and guardrails to ensure reliability and compliance • Collaborating with data and platform teams to operationalize AI—not just prototype it Deep ML expertise is not required —we’re looking for strong engineers who understand how to apply AI capabilities in real products . Take the first step toward your dream career. Here is what we ar