Lilly Posted September 10, 2026

Agentic Automation Lead - Frontier AI

South San Francisco, California, United States of America FULL_TIME
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Lilly is the source of truth for this posting and owns the application process. We surface normalized context and market comparison you won't find on the original listing.

About this opportunity

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.

Where AI Meets Medicine: Build the Future of Drug Discovery in the Heart of Silicon Valley!

Making medicine that’s never been made means doing what’s never been done. If you’re an engineer, scientist, or builder who thrives on problems no one has solved before, this is your invitation, we want you on the team. We are ready to challenge the status quo and push medicine forward, all in the name of health. Are you up for the challenge? If so, join us!

About the Lilly and NVIDIA Partnership

Lilly and NVIDIA are launching a new AI co-innovation lab in the heart of Silicon Valley, an up-to-$1 billion, multi-year commitment to solve drug discovery’s toughest challenges. The lab brings Lilly scientists, technologists, chemists and biologists together with NVIDIA engineers under one roof. Together, we are building purpose-built foundation and frontier AI models trained on Lilly data at scale, tightening the feedback loop between automated wet labs and computational dry labs, designing the next generation of medicines for millions of patients across the globe.

Position Summary

We are looking for an experienced Automation AI Scientist to design and build the agentic systems that plan, execute, and learn from physical experiments. You will own the decision layer of the closed-loop lab: the agents that reason over experimental context, select the next experiment, dispatch it to robotic and analytical platforms, interpret the readout, and update their own strategy, with scientists in the loop at the points where judgment matters.

This is an on-site hands-on scientific engineering role with technical leadership scope. You will prototype rapidly against real instruments and real chemistry, productionize what works, and partner with chemists, biologists, automation engineers, and our NVIDIA counterparts to compress Design-Make-Test-Analyze cycle time from weeks to days. You will also lead a small team of scientist-engineers, set the technical direction for the agentic automation platform, and be accountable for it as a product that other teams depend on, not a collection of prototypes.

Key Responsibilities

Agentic System Design

Design and build multi-agent systems with robust orchestration, state management, error recovery, and tool integration for laboratory workflows

Build the translation layer between high-level scientific intent and low-level instrument control across automation platforms (Hamilton, Tecan, Opentrons) and analytical instruments (LC/MS, NMR, HPLC)

Closed-Loop Science

Implement active learning, Bayesian optimization, and reinforcement-learning approaches for autonomous experiment selection under real-world cost and throughput constraints

Instrument the loop end-to-end so every experiment produces model-ready data in ELN/LIMS and downstream training corpora

Solution Deployment

Partner with automation engineers and scientists to transition prototypes into reliable, monitored lab operations

Deploy and maintain containerized services using Docker and Kubernetes with GitOps and CI/CD practices

Technical Leadership & Platform Ownership

Lead and grow a small team of scientist-engineers: set technical direction, run design and code review, and hold the bar on engineering quality

Own the agentic automation platform end to end: roadmap, architecture, reliability, adoption, and deprecation decisions and be accountable for the outcomes it delivers to scientists

Translate scientific and business priorities into a sequenced technical plan, and communicate progress, trade-offs, and risk to senior R&D leadership

Collaboration & External Engagement

Work directly with NVIDIA researchers and engineers and with partner teams across the AI@Lilly community

Evaluate external vendors, open-source projects, and academic collaborations for strategic fit

What Success Looks Like

Autonomous agents reliably execute multi-step experiments on physical laboratory instruments without babysitting

Measurable reduction in DMTA turnaround attributable to autonomous planning and execution

The team you lead grows in capability and autonomy, with people you mentor taking ownership of major platform components

Basic Qualifications

PhD (or MS + 3 yrs / BS + 6 yrs equivalent experience) in Computer Science, Chemical Engineering, Robotics, Chemistry, Computational Biology, or a related discipline

5+ years of applied experience building AI or algorithmic decision systems, including production LLM agent or multi-agent systems

At least one year of direct people management experience

Preferred Qualifications

Demonstrated experience integrating software control and/or AI systems with laboratory automation platforms (liquid handlers, analytical instruments, robotic workflows)

Track record of owning a platform or product end to end: defining the roadmap, shipping it to real internal or external users, operating it in production, and iterating based on adoption and feedback

Track record with self-driving labs, autonomous experimentation, or high-throughput experimentation (HTE) workflows

Working knowledge of LIMS/ELN engineering and scientific data models in a regulated or GxP-adjacent environment

Experience hiring and building a team from an early stage in a startup, skunkworks, or newly formed function

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 (AMECA), Black Employees at Lilly (BE@Lilly), Chinese Culture Network (CCN), EnAble, Evolve, Lilly Indian Network (LIN), Organization of Latinx at Lilly (OLA), Pride (LGBTQ+ Allies), Veterans Leadership Network (VLN) and Women’s Initiative for Leading at Lilly (WILL).

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

$193,500 - $338,800

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

Job details

Seniority
Not listed
Function
Manufacturing & CMC
Therapeutic area
Not listed
Location
South San Francisco, California, United States of America
Employment type
FULL_TIME

How this role compares

Computed from every other active Manufacturing & CMC role in our database, not just this employer's listings.

We currently track 2402 comparable Manufacturing & CMC roles across 163 biopharma companies.

2402Comparable roles tracked
2290Currently active
163Companies hiring similar roles
52Countries represented

Salary context

651 of 2402 peers report a salary range (USD, annualized)

Peers share this role's job function. This posting doesn't list a seniority level, so peers aren't narrowed by seniority either -- the range below may span more levels than usual.

This roleSubject $193,500/yr – $338,800/yr
Highest disclosed · Executive Director, CMC Regulatory Science · ModernaTX, Inc. $224,900/yr – $404,600/yr
Peer group range $0 – $314,750 (median $123,600)

Where these roles are based

Top locations among the 2402 comparable roles

United States1162
India150
Germany117
France91
Netherlands89
Ireland85

+ 46 more countries

Seniority mix

1099 of 2402 peers have a known seniority level

Senior324
Manager248
Associate131
Intern/Fellow/Postdoc110
Principal92
Director82
Associate Director74
Senior Director31
Executive/VP7

Therapeutic area mix

12 of 2402 peers have a known therapeutic area; the rest are genuinely unlabeled, not hidden

Vaccines & Infectious Disease9
Rare Disease2
Oncology1

Similar opportunities

The closest matches from our peer group, ranked by how similar they are, not how well you'd qualify for them -- treat this as market context, not a guaranteed shortlist; a weak match is labeled as one below.

40%similar
AstraZeneca New Haven, Connecticut, United States of America
Same function Same country
40%similar
40%similar
Lilly Indianapolis, Indiana, United States of America Senior Director
Same function Same country
40%similar
Lilly Indianapolis, Indiana, United States of America Director
Same function Same country
40%similar
Lilly Indianapolis, Indiana, United States of America Director
Same function Same country
40%similar
Lilly Louisville, Colorado, United States of America Principal
Same function Same country

Notify me about similar jobs

Get an email when we spot other openings like this one – same job function, comparable seniority, roles you'd actually want to see.

How we calculate "similar"

No black box, no LLM guesswork: a deterministic score built from four normalized attributes. Here's this role's own peer group at different match levels, so you can see the mechanism, not just the result.

Every comparison starts from the same 100-point budget: 25 for working in the same function, 40 for the same therapeutic area, 20 for the same or adjacent seniority, 15 for the same country. A dimension we can't confirm on both sides contributes nothing, never a guess, never a free pass.

40%
Development Scientist III, Analytical Development and Clinical Quality Control
AstraZeneca · New Haven, Connecticut, United States of America · Seniority not listed
Function Therapeutic area Seniority Country
40%
Director, Analytical Chemistry - Peptides
Lilly · Indianapolis, Indiana, United States of America · Director
Function Therapeutic area Seniority Country
40%
Advisor, Data Scientist - CMC Data Products
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Function Therapeutic area Seniority Country
40%
Scientist - Molecular Biology, Cell Culture Upstream Process Development
Lilly · Indianapolis, Indiana, United States of America · Seniority not listed
Function Therapeutic area Seniority Country
Unmatched or unknown dimensions score exactly the same: 0 points, never a partial guess. A role we know almost nothing about beyond its function bottoms out at 25%; it never inflates to 100% just because there's little to compare against. Seniority uses a defined ladder (Associate → Manager → Associate Director → Senior → Principal → Director → Senior Director → Executive/VP) so "Director" and "Senior Director" count as adjacent, but "Director" and "Executive/VP" do not.