{"id":2453376,"url":"https://alion.io/job/parallel-biosystems-head-of-platform-bioengineering-assay-development","title":"Head of Platform Bioengineering & Assay Development","company":{"id":2230112,"name":"Parallel Biosystems","domain":"parallel.bio","url":"https://alion.io/company/parallel-bio","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"Leadership","role_family":"Leadership","seniority":"head","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":203000,"max":229000,"currency":"USD","period":"year","gross":null,"usd_annual":229000},"salary_estimate":null,"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Go","optional":false}],"status":"live","first_seen_at":"2026-08-31T18:27:31Z","employer_posted_date":"2026-08-31","last_verified_at":"2026-10-18T04:40:10Z","board_verified":true,"closed_at":null,"days_open":47,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":47},"description":"The Mission\nDrug discovery has a translation problem: more than 95% of drugs that succeed in animal models fail in humans. We're building the alternative: human-first drug discovery, powered by organoids and AI, running on real human biology from the very first experiment.\nOur platform is 87% concordant with clinical patient data - a vast improvement over the 3% translational success rate of animals. We’ve demonstrated the ability to model immunotoxicology, immunogen stimulation, and two autoimmune diseases with more on the way. Numerous pharma partners including 3 Fortune 500 companies are already using the platform. We've raised ~$30M from AIX Ventures, Marc Benioff, Jeff Dean, and Y Combinator. With the FDA Modernization Act 3.0 and the FDA's March 2026 validation framework, the regulatory tailwinds only continue to get stronger.\nThe opportunity ahead of the company is generational: build the first scaled engine for generating real human biological data, and use it to fundamentally change how medicines are discovered.\nThe role\nAs Principal Scientist, you will lead the science at our San Francisco site.\nYou will manage our team of scientists and research associates, set experimental strategy, and own the scientific decisions that determine where we invest our experimental effort. You will remain personally at the bench on the hardest problems.\nYour first priority is scientific: deepening our understanding of how our organoid models behave across donors, conditions, and operators, building the reference data and controls that let the team interpret results with confidence, and bringing that rigor to the workflows running at the site. From that foundation, you will own assay development and maturation, technology transfer from R&D, control strategy, characterization, optimization, and readiness for routine execution on the platform.\nYou will also serve as the scientific lead for our external partner programs, designing them well, interpreting them rigorously, and standing behind the results with our partners.\nWhat you'll own\nScientific leadership\nLead the scientific team at our San Francisco site, including hiring, managing, and developing scientists and holding a high bar for experimental rigor and pace.\n\nSet scientific direction and experimental strategy for the platform, and bring competing interpretations to a clear conclusion.\n\nRun regular data review with the team, distinguishing biological effects from technical or process effects and driving toward the experiment that resolves the question.\n\nEstablish high standards for experimental design, controls, documentation, reproducibility, and scientific decision-making, and hold the team to them.\n\nFacilitate productive scientific disagreement and reach clear conclusions quickly, without suppressing dissent or letting debate stall the work.\n\nServe as the scientific lead for external partner programs, from experimental design through data delivery.\n\nRemain close to the bench and personally engage in difficult experimental and troubleshooting work.\n\nAssay and process development\nBuild biological systems from first principles, taking models from concept to working, characterized assays, and deepening the ones already running.\n\nOwn the development and maturation of biological assays and workflows intended for execution on the Parallel Bio platform.\n\nTranslate early R&D assays into robust, repeatable, scalable experimental processes.\n\nDevelop and execute characterization and optimization strategies for complex organoid and cell-based assays.\n\nIdentify critical assay and process parameters and understand how they influence biological outputs.\n\nDesign experiments that establish appropriate operating ranges, robustness, and sources of variability.\n\nLead troubleshooting of complex biological and process failures using structured, hypothesis-driven experimentation.\n\nTechnology transfer and platform readiness\nDefine and build the framework for transferring assays and biological processes from R&D into development and ultimately routine Technical Operations.\n\nDefine clear entry and exit criteria for each stage of assay maturation and technology transfer.\n\nEstablish objective acceptance criteria for platform readiness, including controls, expected ranges, reproducibility requirements, and system suitability.\n\nEnsure transferred assays have sufficient documentation, reference data, controls, and scientific understanding to support reliable execution.\n\nPartner with Technical Operations to ensure new processes can be executed reproducibly by trained operators rather than only by their original developers.\n\nLead or support comparability studies when assays, instruments, workflows, reagents, software, or biological inputs change.\n\nScale-up and robustness\nDevelop strategies for scaling biological workflows from small exploratory experiments into higher-throughput platform processes.\n\nUnderstand and reduce variability introduced by operators, instruments, automation, reagents, donors, biological materials, and environmental conditions.\n\nEstablish appropriate process controls and monitoring strategies for complex biological workflows.\n\nPartner with automation and software teams to translate manual scientific workflows into automated, observable, and reproducible platform processes.\n\nIdentify where additional automation, instrumentation, software, or process controls will materially improve scientific performance.\n\nBuild processes that balance scientific rigor with throughput, cost, cycle time, and operational complexity.\n\nCross-functional platform development\nPartner closely with R&D to ensure new assays are designed with eventual scale and platform implementation in mind and are ready to tech transfer.\n\nPartner with Technical Operations to establish reliable processes for external project execution.\n\nWork with Platform Software, automation, hardware, and data teams to ensure biological requirements are translated into effective platform capabilities.\n\nContribute to platform roadmap decisions by identifying scientific and process-development capabilities required for future programs.\n\nSupport external pharmaceutical programs by ensuring platform processes are scientifically defensible, reproducible, and appropriate for the questions being asked.\n\nWhat success looks like\nYou will help create a clear path from:\nScientific concept → working model with established reference data → demonstrated assay → characterized process → scalable platform workflow → routine external execution\nTeams will know what constitutes a successful technology transfer and what evidence is required before an assay is considered ready for external work.\nWhen experiments fail or produce unexpected results, we will have the controls, reference data, process understanding, and scientific framework necessary to determine why.\nNew assays will move onto the platform faster because Process Development, R&D, Technical Operations, automation, and software share clear interfaces and expectations.\nAnd as Parallel Bio scales, our biological processes will become increasingly reproducible without losing the complexity that makes human biology valuable.\nDay one, week one, month one\nDay one\nMeet the scientific, Process Development, Technical Operations, automation, software, and platform teams. Immerse yourself in our organoid models, assays, workflows, instrumentation, data, and current external programs.\nWeek one\nGo deep on our models, assays, protocols, instrumentation, and data. Form your own view of how the models behave, where the reference data and controls are strongest, and where additional scientific work will most improve reliability for external execution.\nMonth one\nSet acceptance criteria for our core organoid workflows and build out the reference data and controls that support them. Stand up a recurring scientific review forum with the San Francisco team. Align R&D, development, and Technical Operations on ownership and decision rights, and begin driving focused characterization experiments against the highest-priority gaps.\nWho you are\nA principal scientist. You have led bench scientists directly, developed their scientific judgment, and held them to a standard. You can reconcile competing interpretations among people who report to you and reach a decision without suppressing healthy technical disagreement.\nA deeply experienced experimental scientist. You have spent your career developing complex biological assays and understand how difficult it is to make living systems behave reproducibly.\nA builder and process developer. You ask not only whether an experiment works, but under what conditions, how often, why it fails, how variable it is, and what must be controlled to make it reliable. You enjoy taking something that works in the hands of one expert scientist and making it executable by an organization.\nA rigorous troubleshooter. When data are ambiguous, you design experiments that distinguish competing explanations rather than relying on intuition alone.\nA systems thinker. You understand that biological performance emerges from the interaction of cells, reagents, protocols, operators, instruments, automation, software, and data systems.\nHands-on. You are comfortable setting scientific strategy and equally comfortable going to the bench when a difficult problem requires it.\nComfortable with ambiguity. You can bring structure to immature technologies without imposing unnecessary bureaucracy or pretending uncertainty does not exist.\nMission driven. You are excited by the opportunity to replace animal models with scalable human biology and fundamentally change how medicines are discovered.\nTechnical foundation\nYou hold a Ph.D. in Immunology, Cell Biology, Biology, Bioengineering, Biomedical Engineering, Molecular Biology, or a related discipline, with typically 10 to 15 or more years of relevant experience developing complex biological assays, models, and platforms.\nYou have demonstrated significant experience in several of the following areas:\nDeep immunology expertise and hands-on work with complex human in vitro models, organoids, primary immune cells, or advanced mammalian cell culture.\n\nDirect management of bench scientists, including setting scientific direction, running data review, and developing scientific judgment in a team.\n\nBuilding biological systems from 0 to 1 and adapting them onto automated or higher-throughput platforms.\n\nExperience building Process Development functions or technology-transfer frameworks in an early-stage biotechnology company.\n\nAssay development, characterization, optimization, and technology transfer.\n\nIdentifying and controlling biological and technical sources of variability.\n\nDeveloping assays or processes for automated or high-throughput environments.\n\nTranslating early-stage R&D methods into robust workflows used by other scientists or operational teams.\n\nEstablishing controls, acceptance criteria, reference standards, or system-suitability approaches for biological assays.\n\nLeading technically complex investigations and experimental troubleshooting.\n\nEquivalent combinations of education and experience will also be considered.\nBonus points\nSignificant experience developing organoids, immune-cell assays, advanced human cell models, or other highly variable biological systems.\n\nExperience scaling biological workflows onto automated laboratory platforms.\n\nExperience with Design of Experiments, process characterization, capability analysis, or Quality by Design approaches.\n\nExperience working in regulated, quality-controlled, or highly documented scientific environments.\n\nExperience supporting pharmaceutical or biotechnology partners and translating external scientific questions into executable platform workflows.\n\nExperience partnering deeply with robotics, automation, software, data science, or machine-learning teams.\n\nParallel Bio is building human-first drug discovery: 10x faster, 1000x cheaper, 0 animals killed.\nParallel Bio is...","description_format":"text","description_chars":12237,"description_truncated":true,"requirements":{"experience_years_min":10,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"phd","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Drug Discovery","Biomedical 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