Scientist, Antibody Engineering

About Chai Discovery

Chai Discovery is re-architecting drug discovery by building frontier AI foundation models to design molecules.

The founding Chai team has brought together the leading researchers in this space, with seminal research accomplishments at top AI labs. The team has led AI-for-biology programs at premier labs, co-invented protein language modelling, built state-of-the-art folding algorithms, and sold AI adopted by top-10 pharma companies. The company is backed by top-tier investors, including OpenAI, Thrive Capital, Dimension, Conviction, Lachy Groom, Amplify, and many more.

We’re looking to add a few members to our team of scientists and engineers, who obsess over creating the most powerful AI models for antibody discovery, and turning them into products that can transform how medicines are made.

We’re hiring an Antibody Engineer to play a critical role in developing traditional and next-generation biologics ’ll take in-silico candidates spanning monoclonals, bispecifics, TCEs, engineered cytokines, multifunctionals, and ADC/DAC formats, then design constructs, run expression and purification campaigns, and develop fit-for-purpose assays that read out affinity, specificity, and develop ability. The data you generate will feed directly back into our model-training loop, making your experiments the ground truth that guides every next iteration.

At Chai, we’re entering a pivotal stage. After years of foundational R&D, our models are moving beyond protein structure prediction and into real-world therapeutic engineering. We re now tasking our AI models on a broad spectrum of drug development challenges, at an exciting scale of wet-lab validation.

This is not a typical role — it’s a chance to push the boundaries of drug discovery by building some of the most advanced AI drug design models ever built.

We are seeking a scientist with a deep desire to push the limits of what’s possible in therapeutic design and a restless drive to solve real-world problems and iterate quickly. You should have:

Scientific background

• PhD or equivalent work experience in Biological Sciences, Protein Engineering, Biochemistry, or a related field.

• Hands-on expertise with design and characterization in antibody-based biologics. Nice to have experience across at least one advanced modality (e.g., bispecifics, TCEs, ADCs)

• Proficient in molecular-biology workflows: cloning, transient/stable expression (mammalian or yeast), purification, and quality control

• Familiar with binding and develop ability assays, SPR/BLI, ELISA, flow cytometry, etc..

• Comfortable inspecting structures in PyMOL or similar tools to guide mutagenesis and rational design

Execution & collaboration:

• Proven record of designing clear experimental plans and managing CRO or vendor relationships from SOW through data review

• Able to juggle multiple projects, adapt priorities quickly, and communicate results to computational colleagues in a tight feedback loop

• Ability to manage multiple external collaborations effectively

Mindset

• Enjoys troubleshooting the bench-to-model hand-off and pushing emerging antibody formats into new territory

• Thrives in a fast-moving, cross-disciplinary environment

• Frontier technology: we’re developing the next frontier of AI-driven drug discovery that will fundamentally change how new therapeutics are created.

• World-class team: opportunity to work with world-renowned leaders in the AI x biology and technology ecosystem who have created some of the most impactful advancements.

• Highly competitive compensation: we offer highly competitive salary, equity package, and healthcare and wellness benefits.

• Velocity and ownership: we move incredibly fast, which means continuous learning and career growth opportunities are a guarantee. Every team member owns a significant slice of the roadmap.

Strong team culture: Collaborative and supportive startup culture in a small and high-energy team who are guided by our mission to increase the efficiency of creating new medicines and positively impact millions of lives.