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JobsEli Lilly

Principal Engineer - Scientific Authoring (Frontier AI)

Eli Lilly

Principal Engineer - Scientific Authoring (Frontier AI)

Eli Lilly

5 Locations

·

On-site

·

Full-time

·

1w ago

Benefits & Perks

401(k)

Pension

Healthcare

Dental

Vision

Prescription Drug

Flexible Spending Accounts

Life Insurance

Vacation

Employee Assistance Program

Fitness Benefits

401k

Healthcare

Required Skills

Python

NLP

LLM

Prompt Engineering

RAG

Software Engineering

Version Control

Testing

CI/CD

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.

Position Summary:

As a Principal Engineer in Frontier AI, you will build intelligent systems that transform how scientists create, analyze, and manage scientific documents. You will develop AI-powered tools that assist with manuscript preparation, regulatory submissions, patent applications, and technical documentation, helping researchers focus on science while AI handles the mechanics of scientific communication. You will work at the intersection of large language models, scientific knowledge representation, and document engineering to create systems that understand domain context, maintain scientific rigor, and accelerate the authoring lifecycle.

Research & Innovation

  • Design and implement AI agents for scientific document authoring, including literature synthesis, citation management, and figure/table generation

  • Build retrieval-augmented generation (RAG) systems over scientific corpora, ELNs, and internal knowledge bases to ground AI outputs in factual content

  • Develop domain-specific fine-tuning and prompt engineering strategies for chemistry, biology, and pharmacology content

  • Create tools for automated quality checking: scientific accuracy, consistency, formatting compliance, and plagiarism detection

  • Build multi-agent workflows that coordinate literature search, data extraction, drafting, and revision cycles

  • Solution Deployment

  • Build production-grade authoring applications with robust software engineering practices (version control, testing, CI/CD)

  • Deploy scalable services on cloud-native infrastructure (Kubernetes, AWS) with appropriate guardrails for scientific content

  • Partner with scientists, medical writers, and regulatory teams to integrate AI authoring tools into real workflows

  • External Engagement

  • Represent Frontier AI in internal forums and external AI/NLP research communities

  • Evaluate external vendors, open-source tools, and academic collaborations for scientific authoring capabilities

What Success Looks Like:

  • Measurable reduction in time-to-submission for manuscripts, patents, and regulatory documents

  • AI authoring tools become trusted partners for scientists and medical writers

  • High-quality, scientifically accurate outputs that maintain human oversight and accountability

Basic Qualifications:

  • MS + 1 yrs / BS + 2 yrs equivalent experience in Computer Science, Chemical sciences, Bioinformatics, or related discipline with demonstrated scientific domain exposure

  • 1-2 years applying NLP/LLM techniques to text generation, summarization, or information extraction (including industry post-doc)

  • Hands-on experience with LLM application development (prompt engineering, RAG architectures, agent frameworks)

  • Strong software engineering skills: production-quality Python, version control, testing, CI/CD (GitHub portfolio a plus)

  • Deep experience with ML/NLP frameworks (Py Torch, Hugging Face, Lang Chain, Llama Index)

  • Qualified applicants must be authorized to work in the United States on a full-time basis. Lilly will not provide support for or sponsor work authorization or visas for this role, including but not limited to F-1 CPT, F-1 OPT, F-1 STEM OPT, J-1, H-1B, TN, O-1, E-3, H-1B1, or L-1.

Preferred Qualifications

  • Experience with scientific document formats (La TeX, XML/JATS, regulatory submission standards)

  • Familiarity with biomedical NLP (Pub Med, chemical NER, ontologies like MeSH or ChEBI)

  • Working knowledge of vector databases and semantic search (Pinecone, Weaviate, pgvector)

  • Publications in relevant ML/NLP venues (ACL, KDD, NeurIPS)

Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.

Lilly is proud to be an EEO Employer and does not discriminate on the basis of age, race, color, religion, gender identity, sex, gender expression, sexual orientation, genetic information, ancestry, national origin, protected veteran status, disability, or any other legally protected status.

Our employee resource groups (ERGs) offer strong support networks for their members and are open to all employees. Our current groups include: Africa, Middle East, Central Asia Network, Black Employees at Lilly, Chinese Culture Network, Japanese International Leadership Network (JILN), Lilly India Network, Organization of Latinx at Lilly (OLA), PRIDE (LGBTQ+ Allies), Veterans Leadership Network (VLN), Women’s Initiative for Leading at Lilly (WILL), en Able (for people with disabilities). Learn more about all of our groups.

Actual compensation will depend on a candidate’s education, experience, skills, and geographic location. The anticipated wage for this position is

$ - $

Full-time equivalent employees also will be eligible for a company bonus (depending, in part, on company and individual performance). In addition, 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).Lilly reserves the right to amend, modify, or terminate its compensation and benefit programs in its sole discretion and Lilly’s compensation practices and guidelines will apply regarding the details of any promotion or transfer of Lilly employees.

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About Eli Lilly

Eli Lilly

Eli Lilly

Public

Eli Lilly and Company, doing business as Lilly, is an American multinational pharmaceutical company headquartered in Indianapolis, Indiana, with offices in 18 countries. Its products are sold in approximately 125 countries.

10,001+

Employees

5 Locations

Headquarters

Reviews

3.7

1 reviews

Work Life Balance

3.0

Compensation

4.2

Culture

2.5

Career

4.0

Management

3.0

65%

Recommend to a Friend

Pros

Higher base pay

Higher bonus target

Supervisory experience opportunities

Cons

Less PTO to start

Toxic culture concerns

Uncertainty about future performance

Salary Ranges

46 data points

Senior/L5

Senior/L5 · Advisor - Advanced Analytics and Data Science

2 reports

$202,627

total / year

Base

$155,868

Stock

-

Bonus

-

$202,627

$202,627

Interview Experience

2 interviews

Difficulty

2.5

/ 5

Duration

14-28 weeks

Offer Rate

100%

Experience

Positive 50%

Neutral 50%

Negative 0%

Interview Process

1

Application Review

2

HR Screen

3

Phone/Video Interview

4

Hiring Manager Interview

5

Final Interview/Panel

6

Offer

Common Questions

Behavioral/STAR

Past Experience

Culture Fit

Industry Knowledge

Technical Knowledge