Agentic AI Engineer

We are rebuilding biotech for the AI era. When a breakthrough is delayed, the world waits. Getting a molecule from discovery to patients, or a crop from lab to field, involves thousands of slow, manual, disconnected steps. AI has the potential to change this, compressing decades of R&D work into years. But that only happens when clean, structured scientific data and AI are built into how science gets done. Benchling is the AI platform for biotech R&D. Scientists use Benchling to design experiments, capture structured data, and run AI agents and models directly in their workflows. Over 200,000 scientists around the world trust Benchling to power their most important work, from academic labs to Sanofi, Moderna, and more than half of the world's top 50 biopharma. We’re building an AI scientist for our customers. We can’t do that if we haven’t built the muscle ourselves. AI fluency is the foundation we build on; it's core to how we work, and we're committed to helping every new hire integrate it into their day-to-day. As part of our interview process, you'll complete a brief AI-focused exercise or discussion so we can understand how you think about and use AI to drive impact in your role. Feel free to reference any tools, platforms, or workflows you use today. ## RESPONSIBILITIES

• Shape technical direction and architecture: Define the foundational architecture for enterprise agentic AI at Benchling — orchestration, agent frameworks, tool integrations (including MCP), memory and state management, evaluation, and observability. Make clear build vs. buy decisions across the stack with documented rationale. - Write production code at least half your time, particularly during the team's first year. Stand up the CI/CD, testing, evaluation, and deployment infrastructure for agentic systems — leveraging existing patterns from Benchling's Build organization wherever possible. Graduate prototypes from the AI Product Manager's discovery cycles into hardened, production-grade systems and own production support under a "you build it, you run it" model. - Build for multi-tenant isolation, secrets management, audit logging, payload encryption, role-based access controls, and human-in-the-loop controls calibrated to risk. Partner with Security Engineering on threat modeling for agentic architectures — prompt injection, tool misuse, data exfiltration vectors. - Coach power users and departmental teams on production patterns, develop the criteria that decide which prototypes graduate into enterprise-grade systems, and build the internal-facing developer experience — templates, SDKs, sandboxes — that lets builders outside this team ship safely. - Work closely with our Data, Analytics & Systems team peers on the source-of-truth datasets and pipelines that agentic systems depend on. Engage with department leaders on the workflows we're transforming, and with Benchling's platform and infrastructure teams to leverage existing capabilities rather than build parallel systems. - Set the bar for code quality, testing and evaluation, documentation, and on-call practices. Drive technical hiring through interview loop design, bar-raising in interviews, and representing the team to senior candidates. Mentor engineers on the team and other AI builders across the company. ##