Base Salary
$176k - $265k/yr
Responsibilities
- Define the foundational architecture for enterprise agentic AI, including orchestration, agent frameworks, tool integrations, memory and state management, evaluation, and observability.
- Write production code for at least half of the time during the first year and build the testing, evaluation, deployment, and production-support infrastructure for agentic systems.
- Graduate prototypes into hardened, production-grade systems and operate them under a you-build-it-you-run-it model.
- Design enterprise controls including multi-tenant isolation, secrets management, audit logging, payload encryption, role-based access controls, and risk-calibrated human-in-the-loop controls.
- Partner with Security Engineering on threat modeling for prompt injection, tool misuse, and data exfiltration risks.
- Coach departmental teams and AI power users, establish prototype graduation criteria, and build internal templates, SDKs, and sandboxes.
- Collaborate with data, analytics, systems, product, department, platform, infrastructure, and security teams to deliver cross-functional agentic workflows.
- Set standards for code quality, testing, evaluation, documentation, and on-call practices; drive technical hiring and mentor engineers and AI builders.
Requirements
- 7+ years of professional software engineering experience building production systems with strong systems design fundamentals.
- Hands-on experience building production systems integrating LLMs and/or agentic patterns, including orchestration, tool use, memory and state management, evaluation, and observability.
- Production experience with at least two of Python, TypeScript/Node.js, and Go, with comfort working across the stack.
- Hands-on expertise with LLM APIs, agentic frameworks, RAG over business content, vector databases, workflow automation, and LLM observability and evaluation tooling.
- Track record of building a platform, function, or product area from zero to one and scaling it.
- Experience in regulated or security-sensitive environments and knowledge of encryption, access controls, audit logging, and secrets management.
- Ability to exercise technical leadership independently, set direction, improve design standards, and develop other engineers through influence.
- Product-first approach to software development, strong ownership, and interest in learning more about life science.
- Strong communication skills with technical and non-technical audiences.
- Preferred qualifications include enterprise SaaS, life sciences, or biotech experience; familiarity with LangGraph, MCP, and major model-provider agent SDKs; experience with Temporal, Prefect, or Airflow for long-running or agentic workflows; familiarity with SOC 2, HIPAA, or GxP; experience building internal developer platforms; and experience enabling non-engineers to build with AI tooling.
Benefits
- Remote work arrangement is indicated by the #BI-Remote and #LI-Remote tags.
- Equal opportunity employer with a stated commitment to diversity and inclusion.
Tech Stack
Categories
About Benchling
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.