Your work will directly influence live drug programmes used by chemists around the world. What you build will move from idea to production and into the hands of scientists making irreversible decisions. This is not a demo platform, and it’s not academic research.
The challenge
AI in drug discovery fails far more often than it succeeds.
Not because the models are weak, but because the software foundations are fragile, hard to scale, and poorly aligned with how scientists actually work.
Our client is addressing this by building a co-ideation platform that gives computational and medicinal chemists access to high-quality data and production-ready AI capabilities, without forcing them to become software engineers.
This role exists because building software that scientists can trust, adopt, and rely on requires serious engineering discipline.
The role
This is not a feature-factory engineering role.
You will design, build, and ship production-grade software at the core of an AI-enabled drug discovery platform. You’ll work across the full stack, integrating advanced algorithms into systems used daily by expert users.
You’ll collaborate closely with product managers, ML researchers, and domain scientists, while owning engineering quality, scalability, and reliability for the components you touch.
If you’re used to prioritising speed over correctness, this role will challenge you.
What you’ll actually build
- Design and implement core platform features used by chemists and computational scientists
- Productionise research code and advanced algorithms so they scale, perform, and are reliable
- Build and maintain backend services, APIs, and distributed systems that support AI workflows
- Develop and maintain full-stack systems with clean, well-defined interfaces
- Write readable, testable, maintainable code — and raise the bar through code review and feedback
- Support the transition of experimental ideas into stable, production systems
The level of expectation
You’ve likely done several of the following:
- Shipped production software used by demanding technical or scientific users
- Worked across backend and frontend systems rather than specialising narrowly
- Designed systems that had to scale beyond a single team or use case
- Owned features or systems from design through long-term maintenance
- Worked in environments where ambiguity was normal and documentation came second
If your experience is limited to small internal tools, throwaway prototypes, or tightly scoped tickets, this role will stretch you.
Technical requirements (non-negotiable)
- Strong proficiency in Python and TypeScript
- 4+ years of professional software engineering experience
- Solid understanding of data structures, algorithms, and system design
- Experience building full-stack systems, including:
- Distributed backend services and APIs
- Cloud platforms (AWS or GCP)
- SQL and NoSQL databases
- Ability to reason about performance, scalability, and failure modes — not just make things work
Nice to have (but not required)
- Exposure to cheminformatics, computational chemistry, or machine learning
- Contributions to open-source projects or substantial personal software projects
- Experience working closely with scientists, researchers, or data-heavy domains
If you meet 60% of the above, you’re encouraged to apply.
Who thrives here
- Engineers who want meaningful ownership without founder-level risk
- People who care deeply about correctness, clarity, and long-term quality
- Builders who enjoy working at the intersection of software, science, and AI
Your consultant
As a Senior Recruitment Consultant at Aspire Life Sciences, Julien Funes' expertise lies at the nexus of technology and life sciences. He recruits top Machine Learning and data talent for Biotech and life sciences startups across Europe and North America. He is committed to advancing the industry by sourcing and securing top-tier talent for roles in these critical sectors. His approach enables him to effectively match candidates with opportunities where technological innovation meets life science excellence.