Senior Engineer I, Synthetic Chemistry

Our mission is to make biology easier to engineer. Ginkgo is constructing, editing, and redesigning the living world in order to answer the globe’s growing challenges in health, energy, food, materials, and more. Our bioengineers make use of an in-house automated foundry for designing and building new organisms.

Senior Engineer I, Synthetic Chemistry

Boston, Massachusetts

Our mission is to make drug discovery easier to engineer. Ginkgo datapoints is building small-molecule capabilities that pair automation, high-throughput workflows, and scalable data generation.

Role Overview

We are hiring a Senior Engineer I, Synthetic Chemistry to help build and run next-generation synthetic chemistry workflows for small-molecule discovery at Ginkgo. This is a hands-on role for an early- to mid-career chemist who can execute high-quality synthetic chemistry at the bench while helping translate methods into higher-throughput, automation-enabled workflows.

The ideal candidate brings strong synthetic organic chemistry fundamentals, practical experience with HTE and parallel synthesis, and comfort working at the interface of chemistry, automation, data, and software. Experience with coding or technical workflow development, along with comfort using modern computational and AI-enabled tools to accelerate experimental design, troubleshooting, and knowledge capture, will be highly valuable in this role. You will contribute to compound production, workflow development, and platform scaling in close partnership with automation, ADME, and cross-functional small-molecule teams.

Key Responsibilities

Design and execute multi-step synthetic routes to prepare target molecules, intermediates, and analog series in support of small-molecule discovery programs.

Plan, run, and interpret HTE and parallel synthesis campaigns to accelerate route scouting, condition optimization, and SAR generation.

Translate bench chemistry methods onto automation-enabled workflows, including reagent setup, plate-based execution, control strategies, and workflow QC.

Purify and characterize intermediates and final compounds using standard analytical techniques such as LC-MS, NMR, and related methods.

Troubleshoot challenging reactions and workflow failures, identify root causes, and improve throughput, robustness, and data quality over time.

Maintain clear, accurate electronic laboratory records and experimental documentation suitable for internal knowledge sharing and downstream program use.

Collaborate closely with scientists and engineers across synthetic chemistry, automation, ADME, and data to scope work, communicate progress, and deliver compounds and reaction data on timeline.

Contribute to SOPs, runbooks, and transferable workflow documentation so new methods can be scaled and adopted across the platform.

Minimum Qualifications

Ph.D. in synthetic organic chemistry, medicinal chemistry, or a related field with up to 3 years of relevant industry experience, or M.S./B.S. with equivalent hands-on industry experience.

Strong hands-on experience in synthetic organic chemistry, including route execution, reaction optimization, purification, and structure confirmation.

Demonstrated experience with HTE, parallel synthesis, automated reagent handling, powder or liquid dispensing, or related miniaturized chemistry workflows.

Ability to work independently at the bench while managing multiple experiments and priorities with strong attention to detail.

Basic coding or scripting ability in Python, R, or similar, or clear demonstrated aptitude for computational tooling in a lab setting.

Comfort using digital, computational, and AI-enabled tools to support experiment planning, data interpretation, literature review, and workflow troubleshooting.

Strong written and verbal communication skills, with the ability to document work clearly and collaborate effectively across disciplines.

Preferred Qualifications

Experience translating synthetic chemistry methods from manual execution to automated or semi-automated platforms.

Familiarity with integrated workcells, plate-based workflows, or automated chemistry platforms.

Experience supporting library production, analog expansion, or direct-to-biology workflows in a medicinal chemistry or discovery setting.

Experience using Python, R, SQL, or similar tools for experimental data handling, visualization, or workflow support.

Familiarity with ELN, LIMS, or analysis-ready data workflows and comfort partnering with software, automation, or data teams.

Strong comfort adopting new technical tools quickly, including AI-enabled software used for experimental planning, literature synthesis, documentation, or data review.

What Success Looks Like

Target compounds and reaction data are delivered safely, reproducibly, and on timeline for multiple programs.

HTE and parallel synthesis workflows become more robust, documented, and transferable across the team.

New chemistry methods are successfully adapted to Gi…