Ginkgo Bioworks
Senior Software Engineer, Autonomous Lab
$134K–$190K
Boston, Massachusetts +1 · Senior · Full-time · Posted Jun 17, 2026
- Location
- Boston, Massachusetts
Boston, Massachusetts, United States - Experience
- 5 years of software development experience.
- Education
- Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related technical field, or equivalent practical experience.
- Visa sponsorship
- Applicants must be currently authorized to work in the United States on a full-time basis. The employer is unable to sponsor or take over sponsorship of H-1B visas at this time.
About the job
Build and operate Catalyst, Ginkgo’s software platform for autonomous laboratory workflows, spanning hardware orchestration, APIs, data systems, AI-enabled agents, and infrastructure.
What you'll do
- Own complex software features and components through design, implementation, testing, deployment, and ongoing support.
- Improve system architecture, reliability, observability, and operational practices; contribute to incident response and remediation.
- Collaborate with scientists, operators, and engineering teams, and mentor less senior engineers.
What they ask for
- Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related technical field, or equivalent practical experience.
- 5 years of experience in a software development role, with demonstrated ownership of complex systems or features.
- Strong proficiency in Python; additional language experience may be relevant to the team.
- Experience designing and operating production software such as APIs, services, or systems with real users and uptime expectations.
Nice to have
- Familiarity with laboratory automation, robotics, or scientific instrumentation.
- Experience in one or more areas such as agentic systems, scheduling and optimization, hardware protocols, databases, Kubernetes, cloud infrastructure, or CI/CD.
Pay
$134,300.00 - $189,900.00 USD base salary
Tools
Python, C#/.NET, TypeScript/React, Kubernetes, PostgreSQL, GCP, AWS, Azure
AI focus
Build AI-agent interfaces and infrastructure, including tool surfaces, orchestration, prompt pipelines, evaluation harnesses, and safe, observable AI-enabled workflows; use AI agents and tooling to accelerate software development.
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