Chief Technology Officer — Biologics Platform

The mandate

A biologics company has built an integrated discovery engine combining computational protein design, high-throughput expression and functional screening. The platform has produced several partnered candidates and two wholly owned assets, validating important parts of the thesis. As the company scales throughput and advances multiple programmes, the CTO will ensure that models, assays and data infrastructure support both speed and reproducible learning across campaigns.

The problem became urgent when a priority design series performed strongly in screening but failed to reproduce during transfer to a downstream development laboratory. Investigation found no single error. Method changes, reagent lots, data filtering and undocumented judgement had accumulated across the workflow. The board has paused the next major automation investment and asked for a technical reset before committing further capital to the shared platform or advancing another internally owned asset.

The Chief Technology Officer will own the scientific and engineering system that turns design hypotheses into reproducible molecules and data. The remit covers computational design, laboratory automation, assay technology, research data architecture, experimental standards and platform technical strategy. It does not replace the Chief Scientific Officer’s accountability for therapeutic hypotheses or programme biology. The CTO must create a productive interface where models and experiments challenge one another through trustworthy evidence.

Approximately 420 employees and material partners fall within the wider technology and research perimeter. The role is based on site in Cambridge and reports to the Chief Executive or designated executive sponsor. This urgent, unplanned search follows the reproducibility finding; the board expects immediate control of the affected workflow and a measured investment decision, not a promise that more data or automation will solve it automatically.

Why this seat is open

Technology leadership has been divided among computational research, automation and information teams, each reporting through different executives. That structure supported rapid experimentation but left no one accountable for the integrity and economics of the complete design–build–test–learn cycle. The board created the CTO role after concluding that the gap was systemic rather than attributable to one laboratory or model team.

What you will own

• Establish the technical architecture for the design–build–test–learn loop, including construct identity, sample lineage, protocol versioning, instrument context, analysis code and decision records.
• Lead approximately 420 employees and material partners across computational design, automation, assay technology, research data and platform engineering interfaces.
• Resolve the priority reproducibility failure, determine which results remain decision-grade and reset downstream programme commitments where evidence cannot be recovered.
• Define platform services and service levels for therapeutic teams, separating capabilities that benefit from common standards from experiments requiring deliberate local variation.
• Make the investment recommendation on automation, compute, data and laboratory capacity using throughput, information gain, transferability, utilisation and total-cost evidence.
• Set model-development and evaluation discipline, including training-data provenance, prospective tests, performance drift, human review and boundaries on external or partner data use.
• Build technical transfer between discovery and development laboratories so assay and molecule readiness are assessed before teams or partners accept a candidate.
• Protect scientific challenge and responsible experimentation while ending undocumented method variation that makes results incomparable or irreproducible.

The first 12 months

• Days 1–90: Contain the affected workflow, reconstruct the failed series and identify where provenance or method evidence is insufficient. Establish interim release and transfer criteria, inventory the most consequential platform dependencies and stop capital commitments whose value case assumes unverified throughput or model performance.
• Months 4–9: Implement common identity, protocol and analysis controls across the priority loop; run prospective model and assay evaluations; and clarify platform versus programme ownership. Rebuild the automation case around reproducible information gain. Complete technical reviews of the owned assets and present any necessary sequencing or partnering recommendation.
• Months 10–12: Demonstrate repeatable transfer of at least two design series, improved prospective model performance and shorter time from hypothesis to decision without hidden rework. Secure approval for the selected technology roadmap, retire duplicate or low-value workflows and establish a technical succession bench across computational and experimental leadership.

What the board will measure

• Reproducibility of priority assay and design outputs across runs, operators and receiving laboratories, with material variation explained and controlled.
• Complete lineage from design hypothesis and construct through sample, protocol, instrument, analysis and programme decision for selected workflows.
• Prospective model performance against predeclared criteria, separated from retrospective fit and reported with useful failure analysis.
• Technology investment tied to demonstrated information gain, transfer capacity and programme value rather than theoretical throughput alone.
• Reduction in manual reconciliation, repeat experiments caused by preventable metadata gaps and late transfer failures.
• Clear platform–programme decision rights and a stronger leadership bench, evidenced by timely technical choices without recurring CEO arbitration.

The person

You are a CTO, SVP of platform technology, head of computational and experimental sciences or equivalent leader in biologics, synthetic biology, drug discovery or scientific technology. Across 22–28 years, you have integrated models, laboratory automation and experimental evidence at production research scale. You have controlled at least GBP 150 million of annual technology and research investment and led at least 250 employees.

You have personally governed a reproducibility or translation problem where no single bad actor or failed instrument explained the result. You can discuss assay variability, experimental design, model evaluation, metadata, sample lineage and technical transfer with appropriate depth. You know that standardisation can destroy discovery if applied indiscriminately, and can state which variations should be controlled, measured or encouraged.

Relevant backgrounds include biologics engineering, antibody discovery, protein design, advanced screening, synthetic biology or adjacent scientific platforms. Candidates from general enterprise technology will not fit. Pure research leaders must demonstrate engineering discipline, scalable systems and capital choices; pure platform engineers must demonstrate scientific judgement and credibility with therapeutic teams.

The role requires on-site presence in Cambridge because the system spans physical experiments and computation. International candidates may be considered with a credible UK relocation path. The CTO must be candid about uncertainty, willing to slow a programme when evidence is not transferable and equally willing to remove controls that add ceremony without improving learning.

Compensation and terms

The indicative base salary is GBP 250,000–340,000, with annual incentive and long-term participation. Measures will focus on reproducibility, useful cycle time, transfer success, technology capital productivity and platform contribution to programme value. This is a permanent appointment. Relocation and evidenced forfeited awards may be considered, with timing shaped by the urgent technical reset.

Confidentiality

The company, platform, affected experiments and programme conclusions are confidential. Detailed information will be shared only after the retained-search team confirms fit and the required agreement is signed. Applicants must not attempt to identify the organisation through publications, patents or scientific contacts.

Each response must contain no more than 49 words.