AI powered insights for Pharma, Biotech, and Life Sciences. Backed by Y Combinator.
About the role
Construct a model of pharma. Make relevant evidence accessible through bespoke ontologies, indexing, filtering, and lexical and semantic search. Measure quality alongside latency and cost. Deliver backend systems end to end. Translate product and infrastructure needs into practical plans, write production code, and follow through until it works for customers. Break large projects into useful releases. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- A track record of personally delivering substantial search, backend, or infrastructure projects into production. You can explain what you built, how you shipped it, what failed, and what improved
- Strong engineering fundamentals and comfort moving between application code, database queries, and infrastructure
- Experience operating stateful or distributed services, including queues, concurrency, migrations, and recovery
- Production experience with search, indexing, or retrieval systems, including the effects of freshness, filters, and permissions on results
- Practical judgment: you scope work, choose a useful first version, communicate risks early, and finish the rollout
- Clear communication and thoughtful collaboration with engineers, product partners, and domain experts
More about this role
Argon builds AI software for life-sciences teams doing complex research, analysis, and writing. Our products connect documents, scientific evidence, and company knowledge to help people produce useful, well-supported work.
We’re hiring an experienced backend engineer to own the platform and search systems behind those products. You’ll work directly with the founders and a small engineering team, make consequential technical decisions, and carry projects from an ambiguous problem through implementation, rollout, and production operation.
Construct a model of pharma. Make relevant evidence accessible through bespoke ontologies, indexing, filtering, and lexical and semantic search. Measure quality alongside latency and cost.
Deliver backend systems end to end. Translate product and infrastructure needs into practical plans, write production code, and follow through until it works for customers. Break large projects into useful releases.
Own infrastructure and reliability. Build and operate services on AWS and Kubernetes. Improve deployment tooling, observability, recovery, capacity management, and tenant isolation.
Build our next search platform. Lead the search database evaluation...
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