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Senior Backend Engineer (Search & Infrastructure)

argon ai • United State
Relocation
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Argon is seeking an experienced backend engineer to own the platform and search systems for AI software in the life-sciences sector. The role involves building bespoke ontologies, managing AWS/Kubernetes infrastructure, and leading the migration of search databases. Candidates must have a proven track record of delivering substantial search or infrastructure projects into production.

Key Highlights
Direct ownership of platform and search systems working closely with founders
End-to-end delivery of backend systems from ambiguous problems to production
Leadership of search database evaluation and migration projects
Key Responsibilities
Construct a model of pharma using bespoke ontologies, indexing, filtering, and lexical and semantic search.
Build and operate services on AWS and Kubernetes, improving deployment tooling and observability.
Lead the search database evaluation and migration, including indexing, synchronization, and query APIs.
Build dependable systems for asynchronous workloads handling retries, rate limits, and partial failure.
Extend the platform to support longer-running AI workflows.
Improve service boundaries, shared libraries, tests, and development tools to increase shipping speed.
Technical Skills Required
TypeScript Python Amazon Web Services
Benefits & Perks
Relocation support
Nice to Have
Hybrid search
Relevance evaluation
Private customer deployments
AI workflow infrastructure

Job Description

Argon
  • New York City
  • In person

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.
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