Senior Software Engineer (platform)

About the Job

We’re hiring a full-stack software engineer to build the internal discovery product tying together workflows we have built and optimised over the last 2 years. You will translate real scientific practice into software: designing canonical product objects (project specs, curated datasets, longlists, evidence cards), implementing “scientist-in-the-loop” interfaces, and wiring together bespoke in-house models, bioinformatics tooling and agent workflows into a cohesive experience.

Your first priorities will be:
• Building the core product objects and minimal UX/UI that anchor discovery projects.
• Turning our internally developed data curation tooling into a comprehensive workbench, connecting it to curated/QC’d dataset objects and onboarding workflows.
• Shipping a usable internal Target-ID workflow that supports a near-term enterprise discovery project, while staying aligned to our long-term and internal discovery workflows.

Core responsibilities
• Build and iterate on internal product UX for trait/project specification, dataset curation, interactive target selection, per-target evidence cards and review flows
• Integrate existing scientific tooling (models, bioinformatics etc.) into one unified workflow
• Working with our data team to design and implement the canonical data models / objects that represent discovery work in-product, with strong provenance and versioning.
• Collaborate with scientific leads to ensure workflows match how discovery is actually done, and reduce context switching/noise for scientists.
• Support customer-facing deliverables by ensuring outputs are easy to review, export, and defend.

Additional responsibilities
• Working with founders and our internal product team to translate product requirements into roadmap for a unified trait discovery platform.
Improve developer/scientist experience around debugging, reviewing, and reproducing discovery runs.
• Contribute to engineering standards around scientific traceability and human-in-the-loop checkpoints.

About You

What we’re looking for
• Strong full-stack or backend engineering background with a bias toward building clean, reliable internal tools.
• Experience designing data models / schemas and building product surfaces on top of them.
• Comfort operating in ambiguous product spaces and iterating quickly with end users.
• Ability to bridge disciplines: you should be able to sit with plant scientists and ML engineers, understand the workflow pain, and translate that into software.
• Solid Python skills; familiarity with modern web stacks (React/TypeScript or similar) or willingness to work across the stack as needed.
• Strong attention to correctness, provenance, and reproducibility in systems that generate scientific claims.

Nice to have competencies
• Experience building tools for scientists, biotech teams, or other high-integrity domains.
• Familiarity with workflow/data orchestration (e.g., Dagster), model registries (e.g., MLFlow), or agent frameworks.
• Experience with knowledge/evidence graph-style products or structured reporting systems.
• Interest in plant biology, gene regulation, or crop improvement (not required, but helpful).

About Us

About us
🌽 Safeguarding the future of food
Biographica is on a mission to accelerate the development of more productive, sustainable, nutritious & climate-resilient food sources. To achieve this, we’re building the world’s first ML-driven target discovery platform for crop gene-editing.

🧬 Target discovery for gene-editing
While gene-editing of crops is becoming ever more efficient, identifying which genes to edit and how remains a significant challenge. To overcome this bottleneck, we use cutting-edge deep learning to accurately and efficiently identify high value genetic targets for crop gene-editing. Our approach draws inspiration from advancements in the drug discovery space, incorporating transformers, graphs & causal-ML to build a best-in-class discovery platform for plant sciences.

🧪 Productising discovery
We’ve spent the last two years building rigorous ML and bioinformatics foundations for gene discovery (curated plant databases, reproducible pipelines, bespoke models). Our next step is to turn those foundations into a unified, agent-native product that scientists can use end-to-end: specifying traits, curating datasets, generating long-lists, running deep-dive analyses, and publishing defensible evidence packs for customers. This role sits at the centre of that transition.

👥 Team
Led by co-founders Dom (CTO) and Cecy (CEO), we are now a team of 13, including 2 ML engineers, 2 data engineers, 3 bioinformaticians & 2 experimental scientists. We primarily work together in person from our office in Spitalfields, London, 4 days per week. This role will be based in London, with close collaboration across ML, data and scientific product.

🌱Benefits
• Competitive salary & equity options
• 25 days annual leave & option for 2 weeks work from anywhere policy
• Benefits package
• Career development opportunities as the company scales
• Ownership of ambitious, mission-driven work with real-world impact
• Vibrant, innovative & supportive work environment with a committed team
• Access to conferences, events & professional development resources