---
title: 'Product Manager, AI Platform & Partnerships at Manifold Bio'
canonical: 'https://feeny.ai/job/product-manager-ai-platform-partnerships-manifold-bio-boston-pghg83twvq9t'
type: 'job'
last_seen: '2026-09-13'
---

# Product Manager, AI Platform & Partnerships at Manifold Bio

- **Company:** Manifold Bio
- **Location:** Boston, MA / San Francisco, CA
- **Posted:** 2026-05-03
- **Last confirmed live:** 2026-09-13
- **Apply:** https://job-boards.greenhouse.io/manifoldbio/jobs/5127283007

## Job description

Manifold Bio is a platform biotechnology company pioneering AI-guided protein design and massively multiplexed in vivo screening to unlock tissue-targeted medicines and organism-scale models of living systems. Using proprietary molecular barcoding technology, we screen hundreds of thousands of protein designs simultaneously in living systems, producing in vivo-validated datasets at a scale no one else can match. The datasets power our computational models, which leads to better drug designs, creating a flywheel that gets stronger with every campaign. Our team of protein engineers, biologists, and computational scientists works across this full stack to pursue programs both internally and with leading pharma companies.

Position

Manifold Bio is seeking a Product Manager to serve as the internal product owner for our AI projects, leading the roadmap across key domains including protein design, foundation models, reasoning models, agents, and infrastructure. This role covers both  internal product management and liaising with AI / tech partners., Internal responsibilities include interfacing with the AI team and R&D project managers to translate ambitious AI x biology ideas into shipped internal products and platform capabilities. External responsibilities include developing and nurturing relationships with external AI teams and partners, with an opportunity to flex into business development and strategic transactions. This role works closely with our co-founders, AI/ML leadership, and BD team to turn cutting-edge capabilities into durable platform assets.

## Responsibilities

- Define the product vision, roadmap, and success metrics for Manifold’s AI platform capabilities, including protein design, foundation models, and agents
- Translate internal R&D and AI x biology ideas into concrete requirements and run the operating cadences that drive decisions and accountability
- Own Manifold's strategy for engaging the AI ecosystem; decide which partners to prioritize, what to build with each, and how to sequence engagements
- Coordinate cross-functional execution across AI/ML, protein engineering, biology, and platform teams for partnerships and platform development
- Source, qualify, and close new AI partnership opportunities, leading exploratory conversations through to signed scope
- Own the quality of all external deliverables including reports, decks, and demos, and produce executive-ready memos to align internal stakeholders

Required Qualifications

- 2-5 years of product management, technical program management, alliance management, or BD experience, with at least part of that in AI/ML or computational product environments
- Bachelor's degree in a technical field (CS, engineering, biology, or related); advanced degree a plus
- Demonstrated ability to own complex, ambiguous strategic relationships and drive them to concrete value generating outcomes
- Strong working knowledge of modern AI/ML concepts (foundation models, training and evaluation, agentic systems, scaling laws) and how they apply to scientific and industrial problems specific to drug discovery
- Familiarity with biology, protein engineering, drug discovery, or another applied scientific domain
- Exceptional written communication; ability to produce executive-ready memos, decks, and external deliverables independently
- Track record of running cross-functional execution in matrixed organizations and shipping on aggressive timelines
- Comfort operating in high-ambiguity, fast-evolving partnerships where the product itself is being defined as you go
- Demonstrated handle of agentic coding skills; e.g. ability to rapidly run analyses / generate figures

## Preferred Qualifications

- Experience building or shipping products at a frontier AI lab, AI infrastructure company, or AI-first startup
- Experience structuring partnership terms in collaboration with BD and legal (data rights, IP, joint roadmaps)
- Public writing, talks, or other evidence of unusually strong communication ability
- Experience scaling a partnership function or building partnership operating processes from scratch

If you’re excited to use unique protein technologies to shape an innovative drug development strategy, build meaningful industry partnerships, and contribute directly to our mission of advancing breakthrough treatments, please apply!

Base Salary Range: $165K-275K

This reflects the typical offer range for this role, based on experience, role scope, and internal equity. Final compensation decisions are made using a consistent leveling framework and consider the candidate’s experience, interview performance, and expected impact.

This role is eligible for:

- Annual performance-based target bonus
- Stock options
- Comprehensive medical, dental, and vision coverage
- 401(k) plan
- Flexible paid time off and holidays
- Perks including on-site gym, onsite lunch, and commuter support

Our compensation ranges are reviewed annually to ensure alignment with market trends and internal equity. We value different experiences and ways of thinking and believe the most talented teams are built by bringing together people of diverse cultures, genders, and backgrounds.

## About Manifold Bio

## Company Overview
- **One-liner**: Manifold Bio is a platform therapeutics company building the first AI-guided direct-to-vivo discovery platform to design tissue-targeted biologics.
- **Entity Type**: Private (Series A)
- **Headquarters**: Boston, Massachusetts, United States
- **Founded**: 2019
- **Founders**: Gleb Kuznetsov (CEO), Pierce Ogden (CTO), Shane Lofgren (Head of Business Development)

## Core Business
- **Primary industries**: Biotechnology, Drug Discovery, Artificial Intelligence for Protein Design
- **Target customers**: B2B – large pharmaceutical companies (via partnerships and collaborations) and internal pipeline for novel therapeutics
- **Mission or purpose statement**: “Tissue-targeted medicines, designed in vivo” – building a predictive model of living systems to enable rational design of biologics that precisely reach intended tissues.

## Products & Services
- **mDesign Engine**: Integrated platform combining AI-guided protein design with massively multiplexed in vivo screening to measure pharmacokinetics, biodistribution, and target engagement directly in living systems.
- **mCodes**: Multiplexed protein barcodes decoded via NGS, enabling high-throughput tracking of millions of protein variants in a single experiment.
- **mShuttle Portfolio**: Modular library of brain shuttles engineered and optimized in vivo to deliver payloads across the blood-brain barrier with high specificity and exposure.
- **mBER**: Open-sourced AI model for designing epitope-specific antibodies, validated in million-scale experiments. (SaaS/model, not a product per se)
- **Internal Pipeline**: Tissue-targeted biologic candidates for Alzheimer’s disease, Parkinson’s disease, rare CNS diseases, and cardiometabolic disease.

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed
- **Total Funding**: $78.18M (CBInsights) / $61.4M (Apollo.io) – conflicting reports; latest available data shows multiple rounds including a $15M Series A in April 2024.
- **Notable Investors/Partners**: Playground Global, Fifty Years, Amazon Web Services, and a strategic collaboration with Roche announced in November 2025.
- **Growth Signals**: Headcount grew 58.1% YoY to 54 employees; published a joint study with NVIDIA validating million-scale AI-driven protein binder design; active job postings up 100% monthly.

## Competitive Advantages
- **Direct-to-vivo platform**: Unlike most AI-driven drug discovery companies that rely on in vitro data, Manifold tests protein designs directly in living systems, capturing physiologically relevant properties like PK, biodistribution, and toxicity.
- **Massively multiplexed experimentation**: Proprietary molecular tracking (mCodes) enables simultaneous testing of millions of protein variants against hundreds of targets, closing the loop between generative AI design and experimental validation at scale.
- **High-profile collaborations**: The Roche partnership and NVIDIA validation provide external credibility and access to industry-leading resources.

## Strategic Focus
- **Expanding tissue-specific delivery**: Starting with brain (CNS) through mShuttle, then moving to peripheral tissues (adipose, cardiometabolic).
- **Building the “virtual organism”**: Integrating high-throughput in vivo data to train a predictive model of how biomolecules behave in the body, enabling fully rational design.
- **Deepening pharma partnerships**: Leveraging platform capabilities to co-develop next-generation biologics with partners like Roche.
- **Open-sourcing AI models**: Releasing mBER and other tools to attract talent, drive adoption, and set industry standards.

## Why Work Here
- **Culture**: Flat, science-driven organization where ML engineers, computational biologists, and wet-lab scientists collaborate closely. Emphasis on “hybrid computational/wet lab science” and library-guided design.
- **Growth trajectory**: 58% employee growth YoY, active hiring across AI/ML, protein engineering, biology, and operations – signals rapid scaling.
- **Work environment**: Boston-based (Seaport area), likely office-first with some flexibility; job postings don’t mention remote but roles are Boston-listed.
- **Notable perks**: Opportunity to work at the frontier of AI + biology, access to cutting-edge wet lab infrastructure, and direct impact on pipeline decisions from early discovery through IND-enabling studies.

## Sources
1. [manifold.bio](https://www.manifold.bio/) (Company website)
2. [linkedin.com](https://www.linkedin.com/company/manifold-bio) (LinkedIn company page)
3. [cbinsights.com](https://www.cbinsights.com/company/manifold-bio) (CBInsights profile)
4. [boards.greenhouse.io](http://job-boards.greenhouse.io/manifoldbio) (Careers page)
5. [manifold.bio/news](https://www.manifold.bio/news) (News – Roche collaboration, NVIDIA study)
6. [apollo.io](https://www.apollo.io/companies/Manifold-Bio) (Apollo.io revenue/funding data)

## Other roles at Manifold Bio

- [Senior Lab Operations Associate](https://feeny.ai/job/senior-lab-operations-associate-manifold-bio-boston-9hzaxy9hgc0z) — Boston, MA
- [Scientist II/Senior Scientist, Protein Sciences – Cell Binding Assays](https://feeny.ai/job/scientist-ii-senior-scientist-protein-sciences-cell-binding-assays-manifold-bio-he5xybzbd1mk) — Boston, MA
- [Scientist, Bioconjugation](https://feeny.ai/job/scientist-bioconjugation-manifold-bio-boston-v1hw9b634cb4) — Boston, MA
- [Research Associate / Senior Research Associate, In Vitro Pharmacology](https://feeny.ai/job/research-associate-senior-research-associate-in-vitro-pharmacology-manifold-bio-a5vxzqjbgfkm) — Boston, MA
- [Associate Scientist/Senior Associate Scientist, In Vivo Pharmacology – Study Coordinator](https://feeny.ai/job/associate-scientist-senior-associate-scientist-in-vivo-pharmacology-study-vs7tg31p2che) — Boston, MA
- [Computational Scientist, Assay Development](https://feeny.ai/job/computational-scientist-assay-development-manifold-bio-boston-4qvj0atdygfs) — Boston, MA
- [Sr. Director/VP, Biology](https://feeny.ai/job/sr-director-vp-biology-manifold-bio-boston-f5c0ac39wzn7) — Boston, MA
- [AI/ML Scientist, Protein Foundation Models](https://feeny.ai/job/ai-ml-scientist-protein-foundation-models-manifold-bio-boston-ma-or-san-ndnwdy540hyp) — Boston MA OR San Francisco, CA
- [Senior Director, Biotherapeutics](https://feeny.ai/job/senior-director-biotherapeutics-manifold-bio-boston-s6aww0xdkqqd) — Boston, MA
- [AI/ML Research Engineer](https://feeny.ai/job/ai-ml-research-engineer-manifold-bio-boston-ma-or-san-francisco-0qe65tmrvvjb) — Boston MA OR San Francisco, CA