About Company
Benchling is the leader in cloud-based software for biotech R&D, currently on a mission to “rebuild biotech for the AI era.” Historically, bringing a molecule to a patient involved thousands of disconnected, manual steps. Benchling’s platform centralizes scientific data, allowing over 200,000 scientists—including teams at Moderna, Sanofi, and half of the world’s top 50 biopharma companies—to design experiments and run AI models directly within their workflows. Benchling is the digital backbone for the world’s most critical scientific breakthroughs.
Job Details
| Role: | Software Engineer, Developer Enablement |
| Salary: | UP to $234,557* |
| Location: | San Francisco, CA |
| Job Type: | fulltime |
| Posted Date: | 10/04/2026 |
| Application Deadline: | Apply Soon |
Job Description
The Developer Enablement team is the architect of Benchling’s ecosystem. As a Software Engineer in this group, you are essentially a “Developer Platform Engineer.” Your goal is to build the infrastructure, APIs, and SDKs that allow third-party developers, partners, and internal teams to build applications on top of Benchling. You aren’t just building a product; you are building the “operating system” for the life sciences industry.
Requirements
- Experience: Minimum of 5+ years of professional software engineering experience.
- Technical Core: Strong coding fundamentals with the ability to turn abstract requirements into well-architected, maintainable code.
- Systems Design: Proven experience building scalable, high-performance systems.
- Leadership: A track record of driving high engineering standards (code reviews, testing, version control) and mentoring junior/mid-level engineers.
- Problem Solving: Strategic mindset capable of tackling ambiguous technical challenges with long-term scalability in mind.
- Interest: A keen enthusiasm for the Life Sciences industry and Enterprise SaaS (no prior biotech experience required).
- Location: Ability to work Hybrid in San Francisco (on-site Mon, Tue, Thu).
Roles and Responsibilities
- End-to-End Ownership: Take projects from ideation to delivery, including prototyping and scaling new platform features.
- API/SDK Design: Design and maintain external developer-facing REST, GraphQL, and gRPC APIs and SDKs.
- AI Integration: Support the development of AI-powered agents and implement the Model Context Protocol (MCP) to allow AI to interact safely with scientific data.
- High-Throughput Engineering: Architect APIs capable of handling bulk data ingestion (millions of records daily) with minimal latency.
- Cross-Functional Partnership: Collaborate with Product Managers and Designers to ensure a cohesive developer experience.
- Infrastructure: Contribute to the evolution of event delivery systems and new platform infrastructure.
How to Apply?
Role Summary
The Developer Enablement Engineer is a “Force Multiplier.” At Benchling, your “customers” are other developers. By building robust APIs and the Benchling MCP, you enable an entire ecosystem of scientific tools. In 2026, as biotech shifts toward “Autonomous Labs,” your work on AI Agentic interfaces will be the foundation for how AI discovers the next generation of life-saving medicines.
Company Culture & Insights
Benchling is an “Impact-First” organization. The culture is a mix of high-growth tech energy and scientific rigor. Because the work affects real-world health outcomes, there is a high bar for data integrity and security. The hybrid model (3 days in office) is designed to foster high-bandwidth collaboration that is often required when bridging the gap between complex biology and software engineering.
Benchling Workforce Diversity Statistics (2025/2026 Industry Estimates): Benchling is a leader in SF tech diversity. Based on their ongoing transparency reports and San Francisco tech sector averages:
Benchling is a San Francisco Fair Chance employer, actively considering qualified applicants with diverse backgrounds.
Gender Representation: ~36% Female | ~64% Male (with active initiatives for non-binary representation).
Racial & Ethnic Diversity (Engineering):
White: 44%
Asian: 38%
Hispanic / Latinx: 8%
Black / African American: 6%
Two or More Races / Other: 4%
Why We Recommend This Job
- Recession-Resistant Niche: Biotech R&D is a long-term investment cycle, providing more stability than pure consumer tech.
- The AI Frontier: Working on Agentic Ecosystems and MCP in 2026 puts you at the absolute cutting edge of how AI is being applied to physical sciences.
- High Compensation: A base salary reaching $234k plus significant equity makes this one of the most competitive “Zone 1” roles in the Bay Area.
Career Growth Potential
Staff Engineer (Developer Platform): Leading the global strategy for Benchling’s extensibility.
AI Infrastructure Architect: Moving specifically into the team that builds the models and agentic frameworks for biotech.
Head of Developer Relations/Ecosystem: Transitioning into a strategic leadership role managing partner integrations.
Skills You’ll Gain
| Category | Specific Competencies |
| API Architecture | REST, GraphQL, gRPC, and Versioning at scale. |
| AI/Agentic Tech | Model Context Protocol (MCP), LLM Inferencing APIs, AI Agent Orchestration. |
| Data Engineering | High-throughput ingestion, Cursor-based pagination, Sparse fieldsets. |
| Enterprise SaaS | Multi-tenant security, Life Sciences compliance, Scalable platform infrastructure. |
Salary & Benefits Info
- Base Salary: $173,369 – $234,557 (determined by skills and interview performance).
- Equity: Competitive stock options package (Standard for high-growth SF SaaS).
- Benefits: * Comprehensive Health, Dental, and Vision.
- 401(k) + Employer Match.
- Commuter benefits (essential for the SF Hub).
- Wellness stipends and specialized “Life at Benchling” perks.
Interview Preparation
Frequently Asked Interview Questions
- API Design: “How would you design a GraphQL schema for a complex biological entity that has thousands of relationships (e.g., a DNA sequence with various modifications and parentage)?”
- Scalability: “Walk me through the architecture of an API that needs to ingest 5 million records in under 5 minutes without causing downtime for concurrent scientific users.”
- The ‘Developer’ Customer: “How do you maintain backward compatibility for an external SDK while drastically changing the underlying platform infrastructure?”
- Security/AI: “When implementing the Model Context Protocol (MCP), how do you ensure an AI agent doesn’t accidentally execute a ‘destructive’ action on sensitive scientific data?”
Behavioral & Culture Questions
- Strategic Conflict: “Describe a time you had to ‘push back’ on a product requirement because it compromised the long-term maintainability of the developer platform.”
- Cross-Functional Collaboration: “How do you explain the technical limitations of a new API to a non-technical Product Manager who is focused on a tight customer deadline?”
- Mentorship: “Tell me about a time you helped a mid-level engineer level up. What specific process improvements did you implement to help the team grow?”