Cheiron
Pharma data discovery and integration platform
Agent Engineering Intern
Academic-term interns must work on-site at least 20 hours per week; summer interns should expect full-time work. Relocation assistance may be offered selectively.
About the job
- Currently pursuing an undergraduate or master's degree in computer science, computer engineering, or a related technical field.
- Strong programming fundamentals and experience building a substantial software project, developer tool, backend system, or open-source contribution.
- Hands-on experience building a nontrivial agent, retrieval system, tool-using workflow, evaluation harness, or multi-step automation system.
- Clear personal ownership of the work, including the ability to explain what was implemented, the decisions made, and potential improvements.
- Ability to reason about state, failure modes, grounding, evaluation, and engineering tradeoffs, rather than only prompts and model selection.
- Ability to work fully in person in Los Altos.
- Semester or quarter interns must commit at least 20 hours per week; summer interns should be available full time.
- Design and implement new agent workflows with explicit state, task decomposition, tool use, and typed outputs.
- Build retrieval and citation paths that ground important outputs in source evidence.
- Add evaluation, tracing, retries, observability, and recovery behavior for multi-step execution.
- Build the backend services, data models, APIs, and focused product surfaces required to make the workflow useful.
- Test agent behavior against realistic success cases, failure cases, and incomplete evidence.
- Work directly with engineers and domain experts, demonstrate progress frequently, and make pragmatic scope decisions.
- Experience with Python, FastAPI, Postgres, agent frameworks, retrieval systems, or vector databases.
- Backend, distributed-systems, infrastructure, data-pipeline, or end-to-end product experience.
- Experience with tests, deployment, observability, security, or reliable failure handling.
- Experience building systems involving citations, provenance, human review, or other high-stakes correctness requirements.
- Strong open-source work, prior software-engineering internships, or an independently shipped product with real users.
About the company
Cheiron is a discovery platform used by pharmaceutical companies to organize and analyze data from both internal and external sources. It works by pulling together diverse datasets into one unified system, giving users a clear view of their operations and enabling faster, more informed decisions. The product is delivered as a subscription service, giving pharma teams access to tools that streamline data management and workflow processes. Cheiron’s main differentiator is its ability to consolidate disparate data into a single coherent platform, reducing operational chaos and accelerating decision-making. The goal is to help pharmaceutical companies improve data handling, streamline workflows, and make better, quicker decisions across drug discovery and development.
Company Size
11-50
Company Stage
Seed
Total Funding
$12M
Headquarters
Palo Alto, California
Founded
2024
Get referred to Cheiron
See people who can refer or advise you
Simplify's Take
What believers are saying
- Cheiron said on September 1, 2026 it cleared two security milestones.
- By July 22, 2026, it reached seven of Korea's top 10 biopharma customers.
- Menlo-backed U.S. pilots with global pharmas expand addressable revenue beyond Korea.
What critics are saying
- Veeva, Elsevier, and internal pharma IT teams can copy workflows and bundle distribution.
- Enterprise deployments at Pfizer-scale customers face slow procurement and painful data-integration projects.
- Any security incident would freeze pilots and destroy trust across regulated drug programs.
What makes Cheiron unique
- Cheiron's Life Sciences Knowledge Graph unifies biomedical, regulatory, patent, and commercial data.
- It models a live drug program, not isolated documents, enabling traceable decisions.
- Menlo Ventures' July 22, 2026 seed and Robert Langer validate pharma credibility.
Help us improve and share your feedback! Did you find this helpful?
Benefits
Meal Benefits
Commuter Benefits
Growth & Insights and Company News
6 month growth
↑ 0%1 year growth
↑ 0%2 year growth
↑ 0%A unified OS for drug development: our investment in Cheiron. July 22, 2026 Drug development is one of the hardest problems in the world. It takes a decade, costs billions, and fails 90% of the time. Much of this is a natural consequence of how complex these programs are. A drug in development touches clinical, regulatory, manufacturing, and commercial functions all at once, generating knowledge across each that rarely makes its way into a single shared picture. Even the most talented scientists and program leads end up spending a significant amount of their time hunting down context rather than acting on it. The result is slower timelines, decisions made on incomplete information, and drugs that take longer to reach the patients who need them. This is the problem the Cheiron team set out to solve. Today, we're thrilled to announce Cheiron's $8 million seed round, led by Menlo Ventures, with the backing and strategic support of industry veterans including Moderna co-founder and MIT Institute Professor Robert Langer; former Pfizer Chief Medical Officer Freda Lewis-Hall; Chai Discovery co-founder and CEO Josh Meier; former Starbucks CEO Laxman Narasimhan; and former Apple AI chief John Giannandrea. A drug program, represented as a whole. If we look at what it takes to advance a drug program, at any given moment, a team is simultaneously tracking efficacy signals, monitoring the safety profile, stress-testing the regulatory strategy against precedent, and watching competitors for anything that might invalidate their assumptions. At the heart of this is a single argument - that this molecule treats this disease, safely and effectively - which has to hold up at every stage and is being made across dozens of people, hundreds of documents, and years of accumulated context. Yet none of it is connected. Cheiron built the infrastructure to piece it all together. The platform's Lifesciences Knowledge Graph (LKG) ingests and structures biomedical, clinical, regulatory, patent, and commercial knowledge, then maps it against the specific contours of a customer's program. The result is a drug program you can actually query. For the first time, teams have a single place to see the full state of their program and stress-test it in real time. Is the safety narrative still consistent with the latest data? Does the trial design hold up against recent regulatory precedent? Are there gaps in the evidence package that need to be closed before a submission? Cheiron holds the state of the program so experts can focus on judgment, and every answer is traceable to a source and defensible in a room full of scientists. Cheiron's early traction speaks for itself. In less than six months since launch, the platform has reached more than 20% of Korea's biopharma knowledge-worker base and secured seven of the country's top 10 biopharma companies as customers. Building on this momentum, Cheiron is now running active pilots with leading global pharmaceutical companies as it expands into the U.S. market. A customer-obsessed team. The best founders understand their customers at a level that borders on obsessiveness, and Minseok Bae, Jason Park, and Harshit Gupta have that quality in abundance. They met at Stanford and bring extraordinary technical pedigree across competitive programming, biology, and physics, but what stayed with us after our first meeting was how clearly they saw the problem from the customer's seat, and how relentlessly they'd already moved to solve it. The team has also assembled a deep advisor bench of industry veterans across pharma who have led FDA approvals and built global drug programs from the ground up. Backing the Future of AI and Biology. At Menlo, we've long believed that one of AI's most transformative applications lies at the intersection of AI and biology. Cheiron joins a portfolio we've been deliberately building at this intersection, including Chai Discovery, which is developing foundation models for biology, Phylo, building an IDE for biological design, and Aurora Therapeutics, developing therapies for rare diseases. We're thrilled to welcome Minseok, Jason, Harshit, and the Cheiron team to the Menlo family.
Cheiron, a Los Altos-based startup building an operating system for drug development programs, has raised $8 million in seed funding led by Menlo Ventures. The round included backing from notable industry figures including Moderna co-founder Robert Langer, former Pfizer Chief Medical Officer Freda Lewis-Hall, and former Apple AI chief John Giannandrea. The company's platform uses AI to model drug programs as connected systems, consolidating scattered information from experiments, clinical results, regulatory interactions, and scientific literature. At its core is the Life Sciences Knowledge Graph, which structures biomedical, clinical, regulatory, patent, and commercial knowledge into a single model. Since launching less than six months ago, Cheiron has been adopted by tens of thousands of biopharma professionals. The funding will support expansion of the platform's capabilities across clinical, regulatory, and strategic workflows, and grow the company's engineering and life sciences teams.
PhnyX Lab, a GenAI startup, has successfully closed a $4M seed round through a Simple Agreement for Future Equity (SAFE).
/PRNewswire/ -- PhnyX Lab, a pioneering GenAI startup transforming how life science companies operate, announced the successful close of a $4 million seed...