Protein Engineering Scientist — Antibody & VHH Discovery

Enlaza Therapeutics; San Diego (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

Enlaza Therapeutics in San Diego is seeking a Scientist with protein engineering expertise to drive drug discovery programs. You will design and execute experiments, build antibody and VHH libraries, and push lead candidates toward optimization and characterization.

You will work closely with platform engineering, protein sciences, computational biology, pharmacology, and leadership in a fast-paced, collaborative environment, with ~80% hands-on bench work and strong emphasis on data

Qualifications

• Ph.D. in Molecular Biology, Biochemistry, Bioengineering, Structural Biology, Protein Engineering, or a related discipline, with 0-4 years of relevant hands‑on experience in protein engineering; alternatively, a Master’s degree with significant industry experience in a related field.
• Strong scientific rigor, critical thinking, and problem‑solving skills, with demonstrated experience in protein engineering and/or biologics discovery.
• Extensive expertise in molecular biology techniques, including construct design (Geneious or similar software), molecular cloning, mutagenesis, transformation, and plasmid preparation.
• Hands‑on experience with recombinant protein expression and purification from E. coli, including affinity purification, protein quantification, SDS‑PAGE, Western blotting, and related analytical techniques.
• Experience applying protein engineering strategies to optimize therapeutic antibodies and antibody fragments (including mAbs and VHHs), such as affinity maturation, humanization, and developability optimization.
• Practical experience with binding affinity and kinetics characterization using BLI and/or SPR, including epitope binning studies.
• Proficiency with structural biology and molecular modeling tools such as PyMOL, MOE, or equivalent software for protein analysis, rational design, and library construction.
• Excellent written and verbal communication skills, with the ability to effectively present complex scientific data.
• Demonstrated ability to work collaboratively in a fast‑paced, multidisciplinary environment.

Responsibilities

• Design, construct, and generate antibody and VHH libraries, and perform screening campaigns to identify binders against a variety of protein targets.
• Optimize lead antibody and VHH candidates using protein engineering approaches, including affinity maturation, humanization, developability enhancement, and sequence liability mitigation.
• Coordinate and execute the characterization of screening hits and lead molecules, including sample preparation and/or analysis using LC-MS, analytical SEC, BLI, cell-based binding assays, and other relevant biophysical and functional assays.
• Analyze, interpret, and communicate experimental data; organize results and present findings to cross-functional project teams.
• Maintain accurate and detailed experimental records in electronic laboratory notebooks and data systems.
• Collaborate closely with scientists across discovery, protein sciences, computational biology, analytical, and translational teams to advance therapeutic candidates.
• Contribute to troubleshooting experimental challenges and developing innovative solutions to accelerate project progress.
• This position is laboratory-based and is expected to involve approximately 80% hands‑on bench work.

Skills

Protein engineering

Molecular biology

Antibody engineering

Biologics discovery

Analytical techniques

Data interpretation

Team collaboration

Communication skills

Education

PhD in a relevant field

Master’s degree with industry experience

Tools

PyMOL

MOE

Biophysical instruments (BLI/SPR)

ÄKTA chromatography

LC-MS

Job description

Enlaza Therapeutics in San Diego is seeking a Scientist with protein engineering expertise to drive drug discovery programs. You will design and execute experiments, build antibody and VHH libraries, and push lead candidates toward optimization and characterization.

You will work closely with platform engineering, protein sciences, computational biology, pharmacology, and leadership in a fast-paced, collaborative environment, with ~80% hands-on bench work and strong emphasis on data