Staff Software / AI Engineer
Quick Summary
Drug development shouldn’t be guesswork, not when patients are waiting. Pathos is building a next-generation biotech with AI at the core. Not as a feature,
Drug development shouldn’t be guesswork, not when patients are waiting.
About the Role
~1 min readPathos is building the first AI native biotech platform, one that turns massive multimodal datasets into foundation models, and those models into live agents that materially change how drug development is done. Instead of bolting AI onto legacy pharma systems, we are designing a new stack from the ground up.
- Build AI agents and copilots for internal teams across BD, clinical, computational biology, and lab.
- Build robust data pipelines into a governed warehouse and knowledge graph.
- Build MCP style servers and tooling so agents can safely talk to internal systems.
- Work across the full product lifecycle: prototype, iterate, ship, and maintain.
You have architected and owned a production system end to end, from design through observability, that real users depend on. You have shipped LLM powered workflows in production, not just prototyped them. You know how technologies like LangGraph work and not just use it as a library. You make high judgment technical calls at the system level, not just execute well-scoped tasks. You move quickly, take initiative, and operate with a strong sense of ownership. You like working closely with end users and shaping products from zero to one.
- Roughly 8 or more years of professional software, ML, or product engineering experience building systems that real users depend on. We read this as a signal of demonstrated scope, not a hard gate.
- Fluent in Python and TypeScript in production, and comfortable building full stack applications.
- Experience with production grade APIs, eventing, and data engineering, ideally cloud native on GCP, BigQuery, or similar.
- You own services end to end: architecture, implementation, testing, and observability.
Nice to Have
~1 min read- Prior work on agentic systems at scale, retrieval systems, or ML infrastructure.
- Experience operating in highly regulated environments that use patient and clinical trial data.
This is a hybrid role, requiring 4 days per week onsite, in our NYC Headquarters.
Location & Eligibility
Listing Details
- First seen
- September 26, 2026
- Last seen
- September 27, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 52%
- Scored at
- September 26, 2026
Signal breakdown
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