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Salary: USD 180,000 - 250,000 / annual
Edison Scientific builds and deploys AI scientist agents to accelerate science and the development of new medicines. We are seeking a Protein Engineer to join our Forward Deployed team, working onsite with pharma and biotech partners alongside our engineers and computational biologists.
In this role, you will ensure our AI agents generate biologics design recommendations that are scientifically rigorous, developable, and grounded in real protein engineering principles. You will define benchmarks, stress test agent outputs, and collaborate with our partners' biologics teams to identify where AI can accelerate their engineering and optimization workflows. This is embedded, partner-facing work where you'll build relationships with Protein Scientists, Protein Engineers, and Engineering Leadership to learn how they evaluate and prioritize protein variants, bringing those insights back to our AI team to make our platform smarter about what makes a good candidate.
Key responsibilities include:
- Evaluate and improve AI agent performance on protein engineering tasks including sequence optimization, variant library design, stability and developability prediction, and functional screening strategy
- Build benchmarks and success criteria for biologics-focused agent workflows
- Work directly with protein engineers and biologics discovery teams at partner organizations to deploy AI agents into their engineering pipelines
- Act as the large molecule authority on AI-generated outputs, assessing biological plausibility, manufacturability, and experimental feasibility
- Collaborate daily with Forward Deployed Engineers and Computational Biologists on each account
- Support engagement scoping, success metrics, and technical evaluation with the go-to-market team
REQUIREMENTS:
- Ph.D. in Protein Engineering, Biochemistry, Biophysics, Bioengineering, or a related field
- 5+ years of industry experience in biologics discovery or protein engineering, ideally within a pharma or biotech sponsor organization
- Track record in protein optimization campaigns spanning antibody engineering, enzyme engineering, or other therapeutic protein modalities
- Strong proficiency with protein design and analysis tools such as Rosetta, AlphaFold, FoldX, or molecular dynamics platforms
- Strong foundation in protein structure, function, stability, and the relationship between sequence and properties
- Experience integrating developability, immunogenicity, and expression data into design decisions
- Comfortable working alongside computational biology and structural modeling functions
- Ability to travel domestically 20-40% of the time
PREFERRED QUALIFICATIONS:
- Experience working across multiple modalities
- Python proficiency
- High comfort with ambiguity and fast iteration
- Prior experience in an industry or client-facing research context, outside of academia
