Clinical Development AI Engineer - Advisor

Eli Lilly and Company•Us, IN

About The Position

At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We’re looking for people who are determined to make life better for people around the world. Purpose: The Clinical Development AI Engineer designs, builds, and deploys AI-powered solutions that accelerate the work of statisticians and analytical professionals across the clinical development lifecycle. Working within the Next Generation Analytics (NGA) Acceleration team, this role partners closely with statisticians, statistical programmers, and data engineers to identify and build AI-powered workflows that replace or streamline manual processes. The role spans the full solution lifecycle from opportunity identification through delivery and adoption. Primary Responsibilities: This job description is intended to provide a general overview of the job requirements at the time it was prepared. The job requirements of any position may change over time and may include additional responsibilities not specifically described in the job description. Consult with your supervision regarding your actual job responsibilities and any related duties that may be required for the position. The job tasks listed below outline the scope of the position. The application of these tasks may vary, based upon current business needs.

Requirements

PhD in statistics, biostatistics, computer science or data science.
Demonstrated ability to build AI-powered tools or workflows that solve real problems for end users.
Strong software development skills with experience in at least one of: R, Python, or modern AI/ML frameworks.

Nice To Haves

Experience in pharmaceutical or clinical development settings, with sufficient understanding of clinical trial statistics and operations to have credible conversations with statisticians about their work -- or the curiosity and learning ability to develop this understanding quickly.
Direct experience as a biostatistician or statistical programmer in clinical development.
Hands-on experience with large language models, agentic AI systems, or multi-agent architectures.
Track record of building tools that were adopted by their intended users — not just technically functional.
Familiarity with regulatory expectations around statistical deliverables in drug development (e.g., TFLs, SAPs, CSRs, DMC charters, submission packages).
Experience designing review or quality-control workflows where AI output reliability is critical.
Interpersonal communication skills for effective consultation with statistical and clinical stakeholders.
Self-management skills with a focus on results for timely and accurate completion of competing deliverables.
Creativity, innovation, and demonstrated problem-solving ability.
Experience decomposing complex, multi-step processes into structured, automatable components.
Comfort working in a fast-moving environment where the technology landscape shifts frequently.

Responsibilities

AI Solution Design and Development Partner with statisticians, statistical programmers, and data engineers to identify high-value opportunities for AI-driven automation across clinical development workflows.
Decompose complex analytical and operational processes into components suitable for AI assistance, ranging from straightforward productivity tools to sophisticated multi-agent systems.
Build, test, and iterate on AI solutions — including generative tools, review and quality-checking tools, and integrated workflows that combine both.
Establish appropriate trust and validation standards for AI outputs, calibrated to the risk profile of each use case.
Stay current with the rapidly evolving AI landscape and translate emerging capabilities into practical applications for clinical development.
Communication of Results and Inferences Clearly communicate AI solution capabilities, limitations, and validation results to statistical and cross-functional stakeholders.
Collaborate with team members to document AI tool outputs, methodologies, and performance metrics in a manner suitable for regulatory and scientific audiences.
Present AI solution demonstrations, proof-of-concept results, and adoption progress in group settings and scientific meetings, as well as in one-on-one consultations with key customers.
Assist with responses to regulatory queries related to AI-assisted analytical workflows, as needed.
Therapeutic Area Knowledge Develop and maintain sufficient understanding of disease states, competitive landscapes, and the regulatory environment to build AI solutions that are contextually appropriate and scientifically credible.
Engage with therapeutic area statisticians and clinical teams to ensure AI tools reflect the nuances of specific indications and development programs.
Regulatory Compliance Ensure AI solutions are developed and deployed in compliance with applicable corporate, medical, local, and departmental policies, procedures, processes, and training requirements.
Maintain awareness of evolving regulatory expectations around the use of AI in drug development and incorporate these considerations into solution design.
Perform work in full compliance with assigned training curriculum(s) and applicable quality standards.
AI Leadership and Teamwork Design solutions with reuse and scalability in mind, ensuring they can operate across studies, therapeutic areas, and teams rather than serving a single use case.
Introduce and apply innovative AI methodologies and tools to solve critical problems in clinical development.
Merge technical AI expertise with clinical development knowledge to identify issues, evaluate options, and implement solutions.
Lead AI projects independently and work effectively across functions.
Apply technical expertise to influence business decisions about where and how AI can accelerate development.

Benefits

employees also will be eligible for a company bonus (depending, in part, on company and individual performance).
Lilly offers a comprehensive benefit program to eligible employees, including eligibility to participate in a company-sponsored 401(k); pension; vacation benefits; eligibility for medical, dental, vision and prescription drug benefits; flexible benefits (e.g., healthcare and/or dependent day care flexible spending accounts); life insurance and death benefits; certain time off and leave of absence benefits; and well-being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities).

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