---
title: 'AI Biologist - Biologics Development at LatchBio'
canonical: 'https://feeny.ai/job/ai-biologist-biologics-development-latchbio-san-francisco-35ags5d0ggjd'
type: 'job'
last_seen: '2026-10-20'
---

# AI Biologist - Biologics Development at LatchBio

- **Company:** LatchBio
- **Location:** San Francisco, CA
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-10-20
- **Last confirmed live:** 2026-10-20
- **Apply:** https://jobs.ashbyhq.com/latchbio/d4a8c4d4-e118-4dc7-a134-0180936e4148

## Job description

AI Biologist - Biologics Development Latch builds rigorous scientific benchmarks ([benchmarks.bio](http://benchmarks.bio)) for AI agents across biology. We work with frontier labs and pharma to measure whether agents can handle real biological workflows: the messy, multi-layer reasoning that matters in the field. We’re seeking an AI Biologist to join our TxBench team, pushing what AI can achieve in therapeutic antibody development.

About the Role. You will be the scientific authority on ground truth, testing whether agents can reason like an expert biologics development scientist. The benchmark covers monoclonal antibodies, Fc-fusions, and bispecifics in the window after lead nomination and before IND. AI agents today struggle to interrogate raw analytical traces and preclinical data, separate real quality-attribute failures from analytical artifacts, and make advance, engineer, or kill calls an expert would stand behind. You will work with software engineers and scientists to build the tasks and datasets behind our benchmarks. Your judgment will set the standard agent outputs are held to, including:

Build the task

- Turn real development workflows into file-based tasks with structured outputs and deterministic grading: developability triage, analytical/CMC characterization, PK and FcRn reasoning, immunogenicity, effector function and safety, and first-in-human dose projection
- Write gold-standard answers from raw data, with tolerances that reflect real replicate, integration, and fitting variability
- Curate data fixtures: developability panels, glycan LC-MS, charge-variant CE, intact/subunit MS, SEC-MALS, FcRn/FcγR sensorgrams, concentration-time PK, and immunogenicity and effector assays
- Partner with software engineers to turn your judgment into new workflows

Set the hard calls

- Test whether agents can tell a real liability from an artifact, such as a co-eluting glycan peak, a misassigned charge variant, or a single assay flag not confirmed by orthogonal readouts
- Test whether agents match effector function and affinity to the mechanism, rather than assuming “more is better”
- Test whether agents distinguish linear from target-mediated clearance, and judge a molecule against its target product profile

Judge the agent

- Interrogate agent reasoning step by step, and challenge conclusions that sound right but wouldn’t survive a development review or go/no-go decision
- Pinpoint where agents go wrong: why a step fails, what an expert would do instead, and what evidence would change the call
- Score agent confidence, rewarding explicit uncertainty over overconfident calls

## Requirements

- PhD in protein engineering, biochemistry, analytical chemistry, pharmacology, or a related field
- Hands-on analysis of antibody development data. You’ve done the analysis yourself, not just supervised it
- Deep expertise in at least one area (analytical/CMC characterization, large-molecule DMPK, protein engineering and developability, or non-clinical safety) and working fluency across the others
- Command of how readouts map to critical quality attributes, PK and effector properties, and release or comparability decisions
- Python or R for data analysis, including parsing chromatograms and electropherograms, kinetic fitting, or PK modeling
- AI-ready from day one: daily use of Claude, Cursor, or similar agents, with the judgment to spot where model reasoning is technically correct but scientifically unsound
- Confidence to overrule an AI agent when the evidence demands it, and the openness to update when shown wrong
- Ability to calibrate confidence and communicate uncertainty rather than defaulting to binary calls
- Bonus: antibody format and Fc engineering experience (IgG subclasses, YTE/LS, effector-silencing, bispecific architectures)
- Bonus: familiarity with MAM, ICH Q6B/Q5E, FDA immunogenicity guidance, IMGT, SAbDab, and IEDB

Culture. We practice radical transparency: you’ll know how the company is doing, what’s working, and what isn’t. It’ll always be us against the problem, never each other. We’re opinionated but respectful, and we bring solutions with our problems. You decide how you work; we judge the output. We use AI constantly, so what we reward is original expert judgment, not AI output passed off as your own. You’ll start on the bench that fits your expertise and can move across teams as you build a track record. People who do well here and bring leadership experience can move quickly into senior roles. Outside of work, we have company outings most months, team off-sites, a Latch run club, cycling, boxing, ice skating, and soccer. Feel free to add to the list.

## Compensation & Logistics

- Contract: 1099 (or W-8BEN internationally), no end date
- Pay: guaranteed for weeks 1-4 while you ramp, then paid per certified task. Most people in this position earn $120K–$180K+ (uncapped upside); certify twice the tasks/week, earn twice the pay that week.
- Commitment: full-time, on your own schedule. Most of the team works 40+ hours a week.
- Meetings: a few pod check-ins a week. The rest of your time is yours.
- Location: remote (anywhere), hybrid, or onsite in SF. We prefer onsite.
- Onsite perks: catered lunch and dinner daily, a waterfront office in Mission Bay, and monthly parking when available
- Work authorization: US citizens, permanent residents, and OPT holders. We can’t support STEM OPT extensions or sponsorship.

Interview Process We move fast: about 2–3 weeks from your first call, to offer.

- Intro Screen - Latch Talent Team
- Take-Home Project - HackerRank
- Technical Interview - Member of Technical Staff
- Culture Interview - C-Suite
- Offer

## About LatchBio

## Company Overview
- **One-liner**: LatchBio builds and deploys frontier AI agents for biological data analysis, serving over 300 biopharma and R&D labs worldwide.
- **Entity Type**: Private (Series A; total funding $33.2M)
- **Headquarters**: San Francisco, California, United States
- **Founded**: 2021
- **Founders**: Alfredo Andere (CEO) and Kenny Workman (CTO)

## Core Business
- Primary industry: Biotechnology Research / AI for biology
- Target customers: B2B – biopharma companies, academic R&D labs, and solution providers (kits, assays, instrument vendors)
- Mission: Deploy AI agents into real scientific work to accelerate data analysis and drug discovery

## Products & Services
- **Latch Platform**: A unified, serverless bioinformatics platform that lets scientists run, track, and debug pipelines via an SDK-generated no-code interface. Supports FastQ, CSV, H5AD, TIFF, and other formats. Agents can analyze messy real-world data.
- **Latch SDK**: Python toolchain to define serverless workflows and dynamically generate no-code UIs, removing cloud-infrastructure overhead.
- **agent.bio**: Public, interactive sandbox where frontier AI agents (e.g., Claude 4.8 Opus) analyze biological data. Supports 40+ solution providers.
- **benchmarks.bio**: Open, reproducible benchmarks measuring AI agent performance on spatial, single-cell, epigenomics, and preclinical pharmacology data. Includes papers like scBench-Long, TxBench-PP, etc.
- **White-labeled data analysis**: Solution providers can offer a branded, simpler analysis experience for their kits and services.

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed
- **Key Metric**: Annual revenue of ~$1.0M (LinkedIn estimate); total funding $33.2M
- **Notable Investors/Partners**: Coatue, Lux Capital, Fifty Years, Haystack, Gelt, Backend Capital; individual investors include George Church, Jeff Dean, Hemant Taneja, Laura Deming, Alec Nielsen
- **Growth Signals**: 140% YoY headcount growth (from ~11 to 26 employees); 300+ biopharma and academic teams served; 40+ solution providers onboarded; recent publication of multiple benchmark papers (2025–2026)

## Competitive Advantages
- **First-mover in AI agents for biology**: Combines frontier LLMs with rigorous, verifiable benchmarks tailored to biological data (spatial, single-cell, epigenomics, pharmacology).
- **Open benchmarks & reproducibility**: All benchmarks (e.g., scBench-Long) are published openly, building trust and attracting top talent.
- **White-labeling for solution providers**: Allows kit and instrument vendors to offer AI-powered data analysis under their own brand, creating a network effect.
- **Tight integration with real lab workflows**: Supports common file formats and interfaces with existing pipelines, reducing friction for scientists.

## Strategic Focus
- Continue research and deployment of AI agents for biology, with emphasis on long-horizon tasks and messy real-world data.
- Expand the agent.bio sandbox to more solution providers and biopharma customers.
- Publish additional benchmarks (spatial, preclinical) to establish Latch as the standard evaluator of AI in biology.
- Grow engineering and bioinformatics teams to accelerate platform development.

## Why Work Here
- **Engineering culture**: Small, high-autonomy team where engineers own features end-to-end and see their code impact thousands of scientists the same day. Reading groups on category theory, immunology, and more.
- **Remote/hybrid policy**: Not explicitly stated, but headquarters in San Francisco; office parking subsidized. Likely in-office with flexibility.
- **Notable perks**: Unlimited PTO, 100%-subsidized platinum health plan (Cigna) + 75% for dependents, dental/vision, 401(k), ambitious equity, 12+ meals weekly, annual tech stipend, signing bonus, O-1 visa sponsorship, professional development.
- **Team size**: ~26 employees, with 65% in technical roles (engineering, bioinformatics, research). Flat structure with direct access to founders.
- **Growth trajectory**: Rapid headcount growth and expanding customer base offer career acceleration opportunities.

## Sources
1. [latch.bio](https://latch.bio/)
2. [latch.bio/about](https://latch.bio/about)
3. [linkedin.com/company/latchbio](https://www.linkedin.com/company/latchbio)
4. [cbinsights.com/company/latch-bio](https://www.cbinsights.com/company/latch-bio)
5. [jobs.ashbyhq.com/latchbio](https://jobs.ashbyhq.com/latchbio)

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