Full-Time
Special Projects Manager
Updated on 8/21/2026
LatchBio
11-50 employees
Cloud-based data platform for biotech R&D
Compensation Overview
$160k - $200k/yr
H1B Sponsorship Available
San Francisco, CA, USA
In Person
Fully in-office Monday through Friday.
 Business & Strategy (1) |
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- Experience operating in a human data, artificial intelligence, or software-as-a-service startup.
- A technical, finance, or intensive operational background.
- Ability to communicate extremely concisely.
- Bias toward action and iteration over perfection.
- Ability to quickly learn unfamiliar areas such as customer contracts, complex financial models, infrastructure costs, or engineering hiring plans.
- Ability to work with engineers, salespeople, scientists, operations personnel, designers, and product personnel.
- Build first versions of operational systems and properly optimize fragile existing processes.
- Track burn, forecast runway, pressure-test earnings before interest and taxes margins, analyze tradeoffs, and create real-time clarity on bottlenecks.
- Read, assess, and redline master purchase agreements, data processing agreements, statements of work, and partnership contracts.
- Maintain structured oversight of contractual obligations and evolve policies, controls, and documentation.
- Design operating systems that add clarity and accountability as the company scales without creating unnecessary bureaucracy.
- Move fluidly across human resources, hiring, finance, compliance, legal, product, and engineering to solve cross-functional bottlenecks.
- Operate as a force multiplier for the chief operating officer and chief of staff by sizing up ambiguous problems, imposing structure, and moving them to resolution autonomously.
- Recalibrate execution as priorities shift.
- Genuine enjoyment of this type of operational work and willingness to bring personality to the team.
Latch.bio provides a cloud-based data platform for biotech companies to manage and analyze their data. It stores unlimited raw data, organizes and transforms it, and offers analysis tools, all in one place. The platform also includes workflow orchestration, so teams can set up analyses that automatically run across many computing cores and scale as needed, while the interface makes it easy to view analysis results and make quick decisions. A key feature is a customizable data platform that eliminates the need for separate infrastructure setup and supports strong security for large-scale data processing. Compared with competitors, Latch.bio positions itself as a single, cost-efficient solution that replaces multiple tools and optimizes cloud usage to reduce expenses. Its goal is to help biotech companies move projects forward faster by making data analysis cheaper, simpler, and more accessible.
Company Size
11-50
Company Stage
Series B
Total Funding
$163M
Headquarters
San Francisco, California
Founded
2021
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Simplify's Take
What believers are saying
- A June 2026 report put total funding at $163M, including a new Series B.
- LatchBio's July 2026 benchmarks attracted attention around spatial biology and pathogen surveillance.
- The September 2025 25M-cell spatial atlas deepens vendor integrations and product lock-in.
What critics are saying
- BioSecBench showed frontier agents still fail 50% of surveillance tasks, slowing enterprise adoption.
- OpenAI, Anthropic, and Google bundle workflow agents, shrinking LatchBio's differentiation by 2027.
- If 2026 Series B investors demand hypergrowth, weak enterprise monetization kills the company.
What makes LatchBio unique
- LatchBio owns benchmarks.bio, translating tacit bioinformatics judgment into measurable product.
- Its July 2026 BioSecBench-Surveillance benchmark exposes real workflow decisions across sequencing modalities.
- The platform combines cloud infrastructure, workflow orchestration, and curated data portals for biologists.
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Benefits
Competitive salary
Equity
Medical, dental, & vision insurance
Growth & Insights and Company News
6 month growth
↓ -7%1 year growth
↓ -24%2 year growth
↓ -22%Benchmarking AI agents on pathogen genomic surveillance. A verifiable benchmark for practical decisions about taxonomy, variants, AMR, source tracking, anomaly detection, and engineered sequences in pathogen genomic surveillance workflows. Jul 09, 2026 LatchBio, Inc. introduce BioSecBench-Surveillance, a verifiable benchmark for testing whether AI agents can make the analytical decisions required in pathogen genomic surveillance. The benchmark contains 100 evaluations spanning seven task categories, six sample types, and both short- and long-read sequencing. Agents receive realistic sequencing data and sparse surveillance context, then must choose the right tools, references, thresholds, and analysis paths. Thanks for reading! Subscribe for free to receive new posts and support my work. Motivation. As sequencing volumes increase, genomic surveillance is increasingly limited by analysis. Public health workflows depend on bespoke and sometimes tacit choices about sequence references, databases, filters, normalization, and thresholds. AI agents are promising because they can inspect files, run tools, and iterate through workflows autonomously. But surveillance is a challenging problem. Agents must chain complex scientific and analysis decisions correctly from messy biological context. Main results. LatchBio, Inc. evaluated sixteen model-harness configurations across roughly 4,800 runs. Pass rates ranged from about 14% to 50%, with most frontier configurations clustered between 38% and 50%. Refusals varied sharply by harness and provider, from zero to nearly one-third of tasks. Performance varied most by task and read technology. Performance varied more by task type and sequencing technology than by sample type or assay. Most task categories landed between 35% and 50%, but anomaly detection fell to 20%, with genetic-engineering characterization next at 35%. Long-read datasets were also harder, scoring 26% versus 41% for short-read datasets. Sample type, nucleic-acid target, and assay type moved performance much less: clinical and isolate samples were handled best, wastewater was somewhat worse, DNA and RNA differed only modestly, and shotgun and targeted assays were nearly identical. Failures demonstrate gaps in scientific judgment. Agents usually found reasonable tools, but struggled with scientific judgment. The failures came from choices around how to invoke those tools in context, e.g. selecting the wrong reference, threshold, normalization method, or final interpretation of biological signal. The hardest tasks were open-ended judgement calls where the agent had to decide what mattered without being told what target to look for. Anomaly detection requires deciding whether a weak signal was real or background. Genetic-engineering characterization required deciding whether a sequence pattern reflected deliberate construction rather than native or homologous biology. AI Agents will be core infrastructure for genomic surveillance. LatchBio, Inc. is building toward a future where agents analyze surveillance data as it arrives, fast enough to shape an outbreak response while it still matters. Today's agents might not be reliable enough to do so, but by measuring their capabilities, LatchBio, Inc. get closer to this future. LatchBio, Inc. regularly update its benchmark family with new models: benchmarks.bio. This was a joint collaboration with Aclid, an automation platform for biosecurity and biosafety. LatchBio, Inc. is grateful to its scientific collaborators: Harmon Bhasin, Kevin Flyangolts, Dianzhuo Wang, Evan Seeyave, Arjun Banerjee, Amanda Darling, Joshua Stallings, David Stern, Shawn Higdon, Claire Duvallet, Bryan Tegomoh. Thanks for reading! Subscribe for free to receive new posts and support my work.
Indeed the year of agents in bio!Latch is at $15M RR, up 5x QoQ. Targeting $130M 2026.Closing a Series B now at $500M. https://t.co/554fQWv8rI— Arfur Rock (@ArfurRock) April 29, 2026
LatchBio releases a 25M cell atlas for spatial transcriptomics, covering 45 tissue types, 63 diseases and 11 spatial technologies.
As a first case-study, LatchBio, Inc. is releasing an accelerated version of nf-core/methylseq that uses the GPU aligner Arioc developed by Richard Wilton.
Having already raised over US$28 million, LatchBio is making waves in the world of data management and clinical research; read on to learn more about the company's innovative solutions and how they are helping researchers overcome common bottlenecks!