Software Engineer, Tools and Automation

Role Overview

Benchling is building AI & Data Engineering (AIDE), a small autonomous team within our Security & IT organization. AIDE owns internal AI capabilities, adoption, and source-of-truth data and analytics infrastructure. This is an internal tools and automation role where you act as an internal forward-deployed engineer, building reliable internal systems and integrations.

As the founding engineer for this team, you will own technical direction, architecture, and delivery of the internal tooling and automation portfolio, operating as a hands-on player-coach.

Responsibilities

• Shape technical direction and architecture: Define foundational architecture for internal tooling, integration patterns across our SaaS estate, workflow orchestration, data access, service boundaries, and observability. Own agent architectures (tool integration, state management, evaluation) where workflows call for it.
• Build and ship early portfolio: Write production code at least 50% of the time. Establish CI/CD, testing, and deployment infrastructure. Graduate departmental prototypes into hardened, production-grade systems and own production support under a "you build it, you run it" model.
• Design for enterprise: Build for multi-tenant isolation, secrets management, audit logging, payload encryption, RBAC, and human-in-the-loop controls. Partner with Security Engineering on threat modeling.
• Enable builders across the company: Coach power users and departmental teams on production patterns, set graduation criteria for prototypes, and build developer experience tools (templates, SDKs, sandboxes).
• Partner across functions: Work closely with data analytics peers on source-of-truth datasets and pipelines. Partner with department leaders to turn business pain points into scoped engineering solutions.
• Elevate engineering standards: Set the bar for code quality, testing, evaluation, documentation, and on-call practices. Drive technical hiring and mentor team members.

Qualifications

• 7+ years of professional software engineering experience building production systems, with strong systems design and integration fundamentals.
• Proven track record building internal tools, automation, and systems integrations that colleagues depend on daily.
• Demonstrated understanding of how to optimize workloads across deterministic and non-deterministic capabilities.
• Production experience with at least two of: Python, TypeScript/Node.js, Go; comfort working across the stack.
• Practical experience applying LLMs where they earn their place in a workflow, with strong architectural judgment.
• Track record of taking platforms or product areas from zero to one.
• Experience operating in regulated or security-sensitive environments (encryption, access controls, audit logging, secrets management).
• Comfortable exercising technical leadership independent of positional authority.
• Product-first approach to software development.
• Strong communication skills with non-technical audiences.
• Interest in learning more about life science.

Nice to Have

• Background in enterprise SaaS, life sciences, or biotech.
• Familiarity with LLM orchestration and tool-integration patterns (MCP, agent SDKs).
• Experience with async orchestration (Temporal, Prefect, Airflow) applied to long-running or agentic workflows.
• Familiarity with SOC 2, HIPAA, or GxP compliance as they apply to AI systems.
• Experience building internal developer platforms or internal tools at scale.
• Direct experience coaching or enabling non-engineers to build with AI tooling.
• Model research or ML engineering experience.

Interview Process

As part of the interview process, candidates will complete a brief AI-focused exercise or discussion regarding how you think about and use AI to drive impact.