* Only candidates currently residing in the U.S. are eligible to apply.

Who We Are

Company Overview

PhnyX Lab is on a mission to revolutionize the pharmaceutical and medical industries. We’ve built Cheiron, a generative AI platform purpose-built for pharma, that integrates fragmented biomedical knowledge and deploys domain-specific agents to execute real-world life sciences workflows.

Since launching just six months ago, PhnyX Lab has emerged as the leading GenAI platform in the Korean pharmaceutical ecosystem, achieving 20% market penetration across national regulatory authorities and top-tier drug development organizations. We are now scaling globally, with active traction across U.S. and Korean academic institutions, biotech companies, and biopharma partners. We have been part of Stanford StartX Fall ‘25 and over the course of the last 6 months have formed various strategic partnerships with major industry players, including Triple Ring and Stanford SPARK.

All of this has been achieved pre-VC, backed instead by a $6M+ raise from leading angels, including several international tycoon families like SK and Samsung, and AI technologists like Aidan Gomez and Illia Polosukhin.

We’re now growing our core team in the Bay Area and are looking for exceptional AI and software engineers to join as founding engineers. If you're excited to shape core infrastructure, ship cutting-edge GenAI products, and build systems that will redefine how pharmaceutical companies work, reach out!

LinkedIn: https://www.linkedin.com/company/cheiron-bio/

News: Yahoo! Finance, The Korea Herald

Key Responsibilities

As an AI/Backend Engineer, your primary focus will be upgrading our agentic workflow pipeline so it can consistently do real work end-to-end—especially for search-centric tasks that involve multiple data sources.

• Design, build, and maintain robust agentic workflows that can plan tasks, call tools/APIs, and execute multi-step jobs reliably.
• Own long-context behavior across workflows: summarization, context packing, source selection, and memory/state strategies.
• Build and improve retrieval systems end-to-end: data sourcing (scraping/ingestion), storage, embedding/indexing, retrieval quality, and multi-source fusion.
• Implement reliability and quality mechanisms (guardrails, fallback strategies, observability, regression testing) so the system is predictable in production.
• Define evaluation metrics and testing protocols for workflows (success criteria, correctness, latency/cost tradeoffs).
• Analyze failures, document findings, and communicate recommendations to technical and non-technical stakeholders.
• Iterate quickly: prototype improvements, ship, measure, and refine.

Key Skill Sets

Strong experience building GenAI product workflows (LLMs, retrieval, tool usage, agents), and you know it’s more than “just a prompt.”

Solid backend engineering skills, including the ability to implement ideas from scratch (Python preferred)

Practical experience integrating APIs and working across multiple data sources/systems.

• A product mindset: you choose pragmatic architectures, ship quickly, and iterate based on real feedback.
• Excellent communication and interpersonal skills, with the ability to collaborate effectively across teams.

Nice to have

• Bachelor’s degree or higher in Computer Science, AI/ML, or related fields
• Published research or active contributions to open-source AI/ML communities.
• Experience in healthcare/biotech/pharma-related problems
• Start-up experience or demonstrated ability to thrive in fast-paced environments.