B

Benchling

Builds research software for life science labs

Head of Enterprise Applications

Full-TimeUpdated on 10/20/2026
$244k - $366k/yr
Expert
San Francisco, CA, USA
HybridOn-site three days per week: Monday, Tuesday, and Thursday.
IT OperationsEnterprise Applications

About the job

Requirements
  • At least 10 years of experience in enterprise or business applications.
  • At least 5 years of experience leading teams in a fast-paced startup environment, including managing managers and owning a budget.
  • Experience owning a multi-platform SaaS portfolio at scale spanning CRM, ERP, HRIS, and the integration layer between them.
  • Deep Salesforce experience, including quote-to-cash and CPQ/RevCloud in a company with complex pricing and packaging.
  • Hands-on familiarity with an integration platform such as Workato, MuleSoft, Boomi, or Tray, and a perspective on running an integration practice.
  • A track record of measurable automation outcomes, including the relevant metric, baseline, and current result.
  • Practical experience applying AI to enterprise application work and judging where it provides value.
  • Experience building internal self-service that reduced request volume and driving business adoption.
  • Experience scaling systems controls through a company's transition to public-company financial reporting, including designing and operating SOX IT general controls across core financial systems, conducting auditable access reviews and change management, automating evidence collection, and working with internal and external auditors.
  • Experience taking over and stabilizing programs mid-flight, including communicating when a committed date needs to move.
  • Strong vendor management experience, including contract negotiation, renewal strategy, and portfolio rationalization with documented savings.
  • Ability to communicate systems tradeoffs to non-technical audiences, including finance and sales stakeholders.
Responsibilities
  • Set the target-state SaaS portfolio, integration standards, and company data-flow patterns; govern platform selection, rationalization, and lifecycle decisions; decide what to buy, build, consolidate, or retire using cost and risk data.
  • Lead high-visibility programs across quote-to-cash, pricing and packaging, and consumption billing; assess programs, shape them to business outcomes, and communicate realistic delivery expectations.
  • Systematically reduce manual delivery work across configuration, change management, testing, release, access review, and ticket triage; set targets, measure work, and report results.
  • Build practical AI into team workflows and platforms in partnership with the AI and Data Engineering team, and assess where models provide value.
  • Expand self-service by building documentation, guardrails, request patterns, and in-product help so Finance, GTM, People, Legal, and CX teams can solve problems safely; measure request deflection.
  • Design and operate IT general controls across platforms carrying financial data, including access provisioning and reviews, segregation of duties, change management, and evidence capture; partner with Finance, Internal Audit, and Trust and Compliance on control design and external audit readiness.
  • Develop existing team members, determine the appropriate full-time and contractor staffing mix, and hire against capability gaps.
  • Partner with Finance, RevOps, Sales, CX, People, and Legal leaders on the roadmap and associated process changes; prioritize openly and explain decisions.
Desired Qualifications
  • Ownership experience with NetSuite, Certinia, or Workday.
  • Experience with Snowflake, Salesforce Data Cloud, or an analytics platform as part of the application data layer.
  • Experience managing a distributed contractor or partner bench alongside full-time staff.

About the company

Benchling builds cloud software for life science research teams, connecting experiment records with biological designs and sample data. Its electronic lab notebook and molecular biology tools let scientists plan experiments, edit DNA sequences, and document results in a shared workspace. Commercial modules add structured sample registries, inventory tracking, and laboratory workflow management so teams can trace research across projects and collaborate on the same scientific record. Companies pay for platform subscriptions and services, and AI features use credits included with subscriptions. Benchling was founded in 2012 and is headquartered in San Francisco, California.

Company Size

501-1,000

Company Stage

Series F

Total Funding

$411.1M

Headquarters

San Francisco, California

Founded

2012

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Simplify Jobs

Simplify's Take

What believers are saying

  • Commercial reach has breadth: Benchling reports more than 1,300 organizations using its research platform.
  • Japan expansion has a foothold: September 2026 Kyowa Kirin was implementing Benchling AI at two research parks.
  • Employee learning has funding: Benchling includes an annual professional development stipend in its benefits.

What critics are saying

  • Model supply depends on partners: Benchling's AI platform accesses models from NVIDIA, Anthropic, and Lilly.
  • Chemistry tools launched selectively: Benchling's August 2026 introduction specified limited availability for its reaction tools.
  • Office flexibility has limits: Benchling requires in-office employees to attend at least three days weekly.

What makes Benchling unique

  • Hardware connections are built in: Benchling Automation supplies over 200 instrument connectors linked to scientific records.
  • Predictions stay attached to research: Benchling Model Hub tracks model inputs, outputs, and run histories inside experimental records.
  • Academic access is broad: Benchling has given free tools to over 200,000 scientists across more than 7,500 institutions.

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Benefits

  • Four months of fully paid parental leave
  • 401(k) plan
  • Remote working stipend
  • Yearly company-wide retreat
  • Monthly gym and wellness stipend
  • Commuter benefits
  • 100% premiums covered for health, dental, and vision
  • Weekly company social events
  • Flexible PTO and company-wide winter holiday shutdown

Growth & Insights and Company News

Headcount

6 month growth

0%

1 year growth

0%

2 year growth

-3%
PR Newswire
Oct 15th, 2026
Benchling launches Science Foundries to run end-to-end R&D workflows with AI agents

Benchling launched Science Foundries on October 15, 2026, a tool that lets AI agents and scientists run entire scientific processes together. Teams choose a goal, such as producing proteins or optimising a lead, and set which steps agents run and when scientists must approve. Agents execute and monitor work, coordinate handoffs, and flag key decisions, all using the same data. In one pharma antibody example, agents design sequences, order constructs from a contract research organisation, run lab work, and analyse results. Several design strategies can run at once. Parabilis Medicines has moved from standalone agents to Foundries for protein production, screening, and lead optimisation. Benchling customers can set up Foundries starting today.

PR Newswire
Oct 15th, 2026
Benchling launches Direct Data Share for two-way, near real-time sync with Snowflake

Benchling has launched Direct Data Share, a feature that keeps scientific data continuously synced between its platform and a customer's Snowflake environment. It is now in public beta for Benchling customers. Experimental data from Benchling lands in Snowflake as ready-to-query tables, refreshed in minutes. Instrument, assay, computational, and third-party data in Snowflake can flow back into Benchling. IT teams need only a one-time setup, with no custom export pipeline to build or maintain. Admins control who can start syncs and manage connections. "The time it takes to sync data from one source to another can't be the choke point for effective decision making," said Derek Halliday, Benchling's head of product. The feature builds on Benchling's AI Connectors, launched earlier this year.

Token Security
Oct 13th, 2026
Introducing the Agentic Universe: AI agent security, written by the people doing it.

Introducing the Agentic Universe: AI agent security, written by the people doing it. Itamar Apelblat Co-Founder & CEO A few months ago, I looked for specific practical guidance on corporate AI security. "Surely," I thought to myself, "there's an in-depth checklist of the agentic actions security teams should be logging." I didn't find one that was actionable enough for my needs. Sure, I could let AI generate one, but how much could I trust it? In this day and age, with content generation so rampant, I've come to value human experience and expertise. Token decided to go one step further than a single asset (which the team did create): an agentic AI security learning center for practitioners, by practitioners. That's how the Agentic Universe was born. With over 20 contributors, many of them CISOs and senior security experts, Token is covering not only the basics, but also technical lessons for experienced practitioners. Token has partnered with leaders from Roblox, Amex GBT, Deloitte, GCM Grosvenor, Crescendo, Williams Rose, Benchling, Cotiviti, and more. The Agentic Universe is a place where new security and identity team members can get up to speed quickly and efficiently, and where existing professionals get practical resources for their day-to-day work. That's why, alongside in-depth articles and videos, Token has actionable checklists that not only tell you what to do but also how to verify it's been done correctly. There are also practical tools, such as its AI Privilege Guardian, which builds permission boundaries. Explorers wanted. Token has built Agentic Universe as a series of interconnected realms. Dive into a specific area or jump between them; there's no wrong way to browse the learning center. * Foundations. New to agent security? Need a refresher? Start here. This section also has a guide to the first 90 days of a new AI security program. * Threats. See how agents get compromised. You'll be surprised at how many attack paths there are, so Token has organized them in a way that makes sense. * Controls. You've seen what can go wrong; now let's learn how to prevent these incidents. There are no bulletproof solutions, but the defensive arsenal is extensive. * Governance. This is more than control at scale. Here's how to ensure you truly own the agentic program during both regular operations and incidents. * Detection & Response. Hands-on, practical checklists for your daily grind. When the flags are green, you're prepared better than most. Help Token create A better Universe. The AI industry is moving faster than pretty much anything before it, and Token is strapping in for a hell of a ride. In other words, this is not a one-and-done project. Token aim to expand the Agentic Universe by adding more content and structured learning paths. Which is why this is also a call to action: See something missing and want to contribute? Drop Token a line! Looking for a specific learning path? Tell Token! And meanwhile, enjoy exploring the Agentic Universe with Token!

EU-Startups
Aug 27th, 2026
Lausanne-based Adaptyv raises €34.35 million Series A to build the automated lab for agentic biology.

Lausanne-based Adaptyv raises €34.35 million Series A to build the automated lab for agentic biology. August 27, 2026 Adaptyv Bio, the Lausanne-based BioTech startup building an automated wet lab for AI-driven protein design, has raised a €34.35 million ($40 million) Series A round. The round was led by Highland Europe, with existing investors Ace Ventures, ByFounders, and Y Combinator doubling down. Ace Ventures led the company's €6.8 million ($8 million) Seed round in late 2024. "AI has made it easy to design proteins. Many teams can now create thousands of candidate molecules for a target in an afternoon. Finding out whether those molecules actually work is still the hard part. That requires a wet lab. But most wet labs were built for a world where scientists tested twenty designs per target, not two thousand. Adaptyv closes this gap," ACE Ventures said. Founded by Julian Englert and Daniel Nakhaee-Zadeh Gutierrez, Adaptyv has built "an automated, AI-native lab" where the process starts with a digital protein sequence and ends with real experimental data. DNA is synthesised in-house, proteins are expressed cell-free, and binding is measured using SPR with built-in quality control. Customers can submit their designs through a web platform, or through an API, allowing AI agents to order their own experiments directly. When ACE led Adaptyv's Seed round in November 2024, the startup had only nine people and a lab that was beginning to see commercial demand. Fast forward to 2026: the team has tripled, revenue has grown roughly 10x, the company has brought DNA synthesis in-house, scaled lab automation, and even launched its Proteinbase competition platform, attracting "680 participants and 10,000 protein designs to one competition." Adaptyv has also shipped a public API now integrated with Boltz, Chai, Cradle, Tamarind, Latent Labs and Benchling. It now counts over 100 customers, including frontier AI labs, top 5 pharma companies and AI-native drug discovery startups. The company recently ran a benchmark with Anthropic, sending 16 targets from its public design competitions to Claude Science and testing the resulting sequences, anonymised. According to the company, 95% of the 1,320 designs were expressed. "Out of 1,320 designs, 354 bound their target, giving Claude an average hit rate of 26.8%. Only a single target yielded 0 binders. Compared to the results of our Protein Design Competitions, Claude's designs had noticeably higher success rates and would have won 5 out 6, yielding tighter binders," reported the company The test showcased how Adaptyv is "becoming the place frontier labs go when they need real-world proof". The company noted that Google DeepMind runs a similar validation loop, Chai Discovery used Adaptyv to validate its Chai-2 zero-shot antibody release, and Roche and Novo Nordisk run therapeutic design cycles roughly 4x faster than their internal pipelines. The new capital will fund two types of growth: horizontal expansion of lab capacity and vertical expansion into harder biology problems. On the horizontal side, the startup plans to roughly triple its lab capacity by the end of 2026 and keep growing through 2027. On the vertical side, it intends to move beyond binding measurements, which is a market estimated to be worth "a few hundred million dollars a year", into developability and full biophysical characterisation, next-generation modalities such as peptides, ADCs and degraders, and eventually cell-based function. For the horizontal expansion, Adaptyv Bio has announced a new lab and office will open in London in the fourth quarter of 2026, alongside an expansion in Lausanne. The company plans to grow its team from 25 to around 60, with a focus on production, automation and software. For its founders, the long-term goal is to build a biological gigafactory with enough automated experimental capacity for AI to learn from physical reality as quickly as it learns from text. Adaptyv's goal is for lab throughput to no longer be the constraint on how fast biology can progress.

PR Newswire
Aug 20th, 2026
Benchling expands into chemistry with new Reactions feature and AI predictions from Inductive Bio

Benchling has expanded its R&D platform to support chemistry alongside biology. The company launched Reactions, a new capability for planning and modelling single-step synthesis, and added predictive models for small molecule R&D from Inductive Bio. Reactions allows chemists to sketch reactions, automatically calculate stoichiometry, and search past reactions by chemical structure. The platform keeps molecules linked to their synthesis history and experimental results. Benchling's Model Hub now includes Inductive Bio's ADMET prediction models, which help chemists predict chemical and pharmacokinetic properties before physical testing. The models placed first in three consecutive OpenADMET blind prediction challenges. Chemistry capabilities are currently in limited availability. Benchling serves more than 1,300 companies worldwide, including Merck, Moderna, and Sanofi.