Advisor​/Sr. Advisor Automation, RNA Therapeutics

Automation Engineer

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 work—but it's work worth doing. If you're driven by purpose and ready to bring your best to work that truly matters for patients, we invite you to join us.

We are seeking an experienced Automation Engineer to design and implement robust automation platforms that integrate scientific instrumentation, robotic automation, and laboratory data management across Lilly's RNA Therapeutics portfolio. This role reports to the Automation Lead for RNA Therapeutics and works within a multidisciplinary automation team responsible for delivering high throughput automated systems that increase the efficiency, reproducibility, and scalability of RNA therapeutic discovery workflows.

The focus of this position is the design and implementation of automation platforms and integrated workcells rather than support of individual instruments, ensuring solutions are scalable, standardized, and deployable across multiple sites.

A key objective of this role is enabling Design Make Test Learn (DMTL) discovery cycles by implementing automation platforms that generate consistent, high quality experimental data with structured metadata capture. These platforms serve as experimental data generation infrastructure supporting downstream analytics and AI and machine learning model development. Automation platforms developed in this role will act as the experimental backbone of the RNA discovery DMTL cycle, enabling the generation of large, high quality datasets required to train and continuously improve AI and machine learning models.

Automation platforms developed in this role will support the generation of high-quality, standardized experimental datasets with consistent metadata capture, enabling reliable downstream analytics and machine learning model training.

The role requires deep expertise in liquid handling automation and experience implementing complex scientific workflows including next generation sequencing (NGS) library preparation and high throughput RNA processing. These automated workflows form a critical part of the infrastructure required to generate clean, reproducible, and unbiased datasets used to train machine learning models.

The successful candidate will partner closely with scientific, AI and ML, informatics, and data engineering teams to translate biological workflows into reliable automated platforms that produce traceable, structured experimental datasets. The ability to work in a collaborative, fast moving environment and adapt to evolving scientific needs is critical.

Responsibilities:

• Partner with internal partners to understand scientific workflows and develop automation solutions that improve throughput, reproducibility, data quality, and the generation of structured experimental datasets.
• Design automation workflows that minimize experimental variability and bias while ensuring consistent metadata capture and traceability, enabling datasets suitable for downstream analytics and AI/ML model development.
• Design, implement, and support laboratory automation platforms including liquid handlers, robotics, and integrated workcells from requirements gathering through deployment and scale up.
• Lead implementation of complex automation platforms including RNA processing systems and next generation sequencing (NGS) library preparation workcells.
• Develop robust liquid handling methods on Hamilton STAR liquid handling platforms including liquid class optimization, assay miniaturization, and workflow standardization.
• Implement integrated automation workcells involving liquid handlers, plate handling robotics, and analytical instrumentation.
• Contribute to the automation strategy and evolve solutions with business needs.
• Find opportunities to improve reliability, efficiency, and scalability of existing automation platforms.
• Implement complex integrated projects while proactively identifying risks and mitigation strategies and communicating progress to partners.
• Work with Lab Operations and IT teams to plan space requirements, installation of automation hardware, and automation supply management.
• Translate biological workflows into automation requirements including data capture, metadata tracking, experiment lineage and integration with digital systems.
• Provide end user training and support for automation systems and digital laboratory platforms including ELN and LIMS systems such as Benchling to ensure consistent workflow execution and high quality experimental data capture.
• Collaborate with interdisciplinary teams including scientists,…