Eli Lilly and Company
AI Software Lead Engineer
Eli Lilly and Company - Indiana, Pennsylvania, us, 15705
Work at Eli Lilly and Company
Overview
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Overview
AI Software Lead Engineer page is loaded AI Software Lead Engineer Apply locations US: Loxo San Francisco Haskins time type Full time posted on Posted Yesterday job requisition id R-88813 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.
AI Software Lead Engineer — Building Agentic AI for Scientific Discovery
What You'll Be Doing:
As the
AI Software Lead Engineer , you'll take a pivotal role in shaping a next-generation platform that leverages
agentic AI and LLMs to accelerate drug discovery —from molecular hypothesis generation to experimental design optimization. This platform is designed to empower scientists across therapeutic areas by combining advanced AI with deeply integrated
biomedical and multi-omics data
spanning single-cell genomics, spatial transcriptomics, proteomics, metabolomics, epigenomics, and phenomics. In this highly hands-on leadership role, you'll apply your software engineering expertise to design, build, and scale systems that support
multi-step scientific workflows
including CRISPR screening analysis, drug-target interaction prediction, and real-time experimental feedback loops, while collaborating closely with domain experts in computational biology, systems biology, structural biology, and chemical biology. This position is ideal for engineers who thrive in building complex systems that integrate cutting-edge omics technologies with AI, are excited by working on problems like multi-modal biological data fusion and automated experimental design, and want to help
push the frontiers of AI-enabled drug discovery
through deep integration of computational and experimental biology. How You'll Succeed: Design, implement, and scale key components of an
agentic AI platform
supporting drug discovery workflows, including target-disease association discovery, compound-protein interaction prediction, and multi-omics biomarker identification. Build modular backend services and orchestration layers that can support
LLM-powered literature mining ,
real-time experimental planning , and
tool-use chains
over scientific data including single-cell RNA-seq, spatial transcriptomics, CRISPR screens, and proteomics datasets. Collaborate with AI scientists and computational biologists to integrate
LLM frameworks (e.g., LangTorch, Semantic Kernel)
with structured biological data sources to enable reasoning across
multi-omics, assay data , protein-protein interaction networks, metabolic pathways, and experimental results from high-throughput screens. Develop intelligent interfaces using React or similar frameworks to support
interactive, AI-guided workflows
for target identification, pathway enrichment analysis, drug-target network exploration, CRISPR hit validation, and automated experimental protocol generation. Ensure data integrity, security, and traceability across workflows that handle
omics, compound, assay data , and sensitive biological datasets including patient-derived samples, with proper provenance tracking for regulatory compliance. Lead development of scalable services deployed via Kubernetes and Terraform in cloud environments (AWS, GCP) optimized for high-throughput computational biology workloads including genome-wide association studies and molecular dynamics simulations. Apply CI/CD, test automation, and observability to enable robust, maintainable deployment pipelines for scientific computing environments supporting real-time experimental feedback and automated hypothesis testing. Collaborate with product managers, computational biologists, and domain scientists to translate evolving scientific workflows into scalable software systems that support cutting-edge omics research and accelerate bench-to-bedside translation. What You Should Bring: Proven experience as a senior software engineer or tech lead, with a strong foundation in backend architecture, microservices, and distributed systems—ideally in scientific computing platforms supporting multi-omics data or high-throughput biological assays. Expertise in Python and proficiency in one or more of the following: Node.js, Go, Java, or Rust. Experience with scientific computing libraries (e.g., NumPy, SciPy, Pandas, BioPython ) and omics analysis frameworks is highly desirable. Hands-on experience building or scaling platforms in cloud-native environments (AWS, GCP, or Azure) using container orchestration (Kubernetes) and infrastructure-as-code tools like Terraform—preferably for computationally intensive biological workflows such as genome assembly or protein structure prediction. Familiarity with frontend development using React or similar frameworks, ideally applied to scientific data visualization or interactive analytics for complex biological datasets. Strong interest in applying software engineering to scientific discovery, which includes areas such as: LLM-powered scientific reasoning for hypothesis generation, literature mining, and protocol optimization AI-driven target identification and CRISPR screening analysis Real-time experimental design optimization using active learning Agentic AI systems for orchestrating multi-step, tool-enabled scientific workflows High-throughput pipeline development for GWAS, single-cell, or multi-modal omics studies Scientific visualization for networks, pathways, and drug mechanisms Feedback loops that connect wet-lab automation with real-time AI-guided experimentation Multi-omics data integration (e.g., scRNA -seq + ATAC-seq, spatial transcriptomics, proteomics/metabolomics co-analysis) Strong communication skills and a collaborative mindset for partnering with cross-functional teams including computational biologists, structural biologists, chemical biologists, and lab scientists. Intellectual curiosity and a growth mindset—especially an eagerness to deepen your understanding of systems biology, experimental design, and AI applications in drug discovery. Basic Qualifications: Bachelor's or Master's degree in Computer Science, Software Engineering, Bioinformatics, Computational Biology, Systems Biology, or a related technical field with coursework in molecular biology, genetics, or biochemistry. 7+ years of experience in software engineering with a track record of delivering robust, scalable platforms, with demonstrated experience in scientific computing environments supporting biological data analysis or experimental workflows. Demonstrated ability to lead engineering projects from architecture to production, ideally in scientific or research environments involving complex biological datasets and multi-step experimental protocols. Organization Overview: Lilly IT builds and maintains capabilities using cutting edge technologies like most prominent tech companies. What differentiates Lilly IT is that we redefine what’s possible through tech to advance our purpose – creating medicines that make life better for people around the world, like data driven drug discovery and connected clinical trials. We hire the best technology professionals from a variety of backgrounds, so they can bring an assortment of knowledge, skills, and diverse thinking to deliver innovative solutions in every area of our business. Research Tech unites science with technology to accelerate the Research and Development of medicines and to deliver therapeutic innovations. The team leverages technology and platforms to streamline scientific experimentation to help Researchers follow the science, to understand the disease and identify potential therapies. They are at the forefront of advanced analytics to enable data driven drug discovery, to innovate so Scientists can rapidly analyze and accelerate the discovery of new medicines. 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), enAble (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 $148,500 - $235,400 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. #WeAreLilly
About Us
At Lilly we strive to ensure our employees are part of a team that cares about them and our shared purpose of making life better for those around the world.How do we do this? We continue to look for ways to include, innovate, accelerate and deliver while maintaining integrity, excellence and respect for people.We hope that you seek to join us on our journey as we create medicine and deliver improved outcomes for patients across the globe!
#J-18808-Ljbffr
AI Software Lead Engineer , you'll take a pivotal role in shaping a next-generation platform that leverages
agentic AI and LLMs to accelerate drug discovery —from molecular hypothesis generation to experimental design optimization. This platform is designed to empower scientists across therapeutic areas by combining advanced AI with deeply integrated
biomedical and multi-omics data
spanning single-cell genomics, spatial transcriptomics, proteomics, metabolomics, epigenomics, and phenomics. In this highly hands-on leadership role, you'll apply your software engineering expertise to design, build, and scale systems that support
multi-step scientific workflows
including CRISPR screening analysis, drug-target interaction prediction, and real-time experimental feedback loops, while collaborating closely with domain experts in computational biology, systems biology, structural biology, and chemical biology. This position is ideal for engineers who thrive in building complex systems that integrate cutting-edge omics technologies with AI, are excited by working on problems like multi-modal biological data fusion and automated experimental design, and want to help
push the frontiers of AI-enabled drug discovery
through deep integration of computational and experimental biology. How You'll Succeed: Design, implement, and scale key components of an
agentic AI platform
supporting drug discovery workflows, including target-disease association discovery, compound-protein interaction prediction, and multi-omics biomarker identification. Build modular backend services and orchestration layers that can support
LLM-powered literature mining ,
real-time experimental planning , and
tool-use chains
over scientific data including single-cell RNA-seq, spatial transcriptomics, CRISPR screens, and proteomics datasets. Collaborate with AI scientists and computational biologists to integrate
LLM frameworks (e.g., LangTorch, Semantic Kernel)
with structured biological data sources to enable reasoning across
multi-omics, assay data , protein-protein interaction networks, metabolic pathways, and experimental results from high-throughput screens. Develop intelligent interfaces using React or similar frameworks to support
interactive, AI-guided workflows
for target identification, pathway enrichment analysis, drug-target network exploration, CRISPR hit validation, and automated experimental protocol generation. Ensure data integrity, security, and traceability across workflows that handle
omics, compound, assay data , and sensitive biological datasets including patient-derived samples, with proper provenance tracking for regulatory compliance. Lead development of scalable services deployed via Kubernetes and Terraform in cloud environments (AWS, GCP) optimized for high-throughput computational biology workloads including genome-wide association studies and molecular dynamics simulations. Apply CI/CD, test automation, and observability to enable robust, maintainable deployment pipelines for scientific computing environments supporting real-time experimental feedback and automated hypothesis testing. Collaborate with product managers, computational biologists, and domain scientists to translate evolving scientific workflows into scalable software systems that support cutting-edge omics research and accelerate bench-to-bedside translation. What You Should Bring: Proven experience as a senior software engineer or tech lead, with a strong foundation in backend architecture, microservices, and distributed systems—ideally in scientific computing platforms supporting multi-omics data or high-throughput biological assays. Expertise in Python and proficiency in one or more of the following: Node.js, Go, Java, or Rust. Experience with scientific computing libraries (e.g., NumPy, SciPy, Pandas, BioPython ) and omics analysis frameworks is highly desirable. Hands-on experience building or scaling platforms in cloud-native environments (AWS, GCP, or Azure) using container orchestration (Kubernetes) and infrastructure-as-code tools like Terraform—preferably for computationally intensive biological workflows such as genome assembly or protein structure prediction. Familiarity with frontend development using React or similar frameworks, ideally applied to scientific data visualization or interactive analytics for complex biological datasets. Strong interest in applying software engineering to scientific discovery, which includes areas such as: LLM-powered scientific reasoning for hypothesis generation, literature mining, and protocol optimization AI-driven target identification and CRISPR screening analysis Real-time experimental design optimization using active learning Agentic AI systems for orchestrating multi-step, tool-enabled scientific workflows High-throughput pipeline development for GWAS, single-cell, or multi-modal omics studies Scientific visualization for networks, pathways, and drug mechanisms Feedback loops that connect wet-lab automation with real-time AI-guided experimentation Multi-omics data integration (e.g., scRNA -seq + ATAC-seq, spatial transcriptomics, proteomics/metabolomics co-analysis) Strong communication skills and a collaborative mindset for partnering with cross-functional teams including computational biologists, structural biologists, chemical biologists, and lab scientists. Intellectual curiosity and a growth mindset—especially an eagerness to deepen your understanding of systems biology, experimental design, and AI applications in drug discovery. Basic Qualifications: Bachelor's or Master's degree in Computer Science, Software Engineering, Bioinformatics, Computational Biology, Systems Biology, or a related technical field with coursework in molecular biology, genetics, or biochemistry. 7+ years of experience in software engineering with a track record of delivering robust, scalable platforms, with demonstrated experience in scientific computing environments supporting biological data analysis or experimental workflows. Demonstrated ability to lead engineering projects from architecture to production, ideally in scientific or research environments involving complex biological datasets and multi-step experimental protocols. Organization Overview: Lilly IT builds and maintains capabilities using cutting edge technologies like most prominent tech companies. What differentiates Lilly IT is that we redefine what’s possible through tech to advance our purpose – creating medicines that make life better for people around the world, like data driven drug discovery and connected clinical trials. We hire the best technology professionals from a variety of backgrounds, so they can bring an assortment of knowledge, skills, and diverse thinking to deliver innovative solutions in every area of our business. Research Tech unites science with technology to accelerate the Research and Development of medicines and to deliver therapeutic innovations. The team leverages technology and platforms to streamline scientific experimentation to help Researchers follow the science, to understand the disease and identify potential therapies. They are at the forefront of advanced analytics to enable data driven drug discovery, to innovate so Scientists can rapidly analyze and accelerate the discovery of new medicines. 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), enAble (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 $148,500 - $235,400 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. #WeAreLilly
About Us
At Lilly we strive to ensure our employees are part of a team that cares about them and our shared purpose of making life better for those around the world.How do we do this? We continue to look for ways to include, innovate, accelerate and deliver while maintaining integrity, excellence and respect for people.We hope that you seek to join us on our journey as we create medicine and deliver improved outcomes for patients across the globe!
#J-18808-Ljbffr