Senior Software / AI Engineer

PathosNew York, NY
1dHybrid

About The Position

Pathos 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’re designing a new stack from the ground up. We’re hiring experienced engineers to architect and ship the first generation of Pathos’ AI and data infrastructure. Your work will power our core products and enable agents that support BD, clinical development, computational biology, and lab teams. This is a ground-floor role with broad technical scope and ownership. If you want to build the technical infrastructure that rewires the R&D workflow, this is the place to do your career’s best work. This will be one of the most direct applications of your technical skills to advancements in cancer research.

Requirements

  • Senior software / ML engineer who can design, build, and ship
  • Have 4+ years of experience as a software/ML/product engineer working on user-facing systems
  • Have built or prototyped LLM-powered workflows using the OpenAI API (or similar)
  • Take initiative, move quickly, and operate with a strong sense of ownership
  • Enjoy working closely with end users and shaping 0→1 products
  • Are collaborative, curious, and motivated to make an outsized impact at the frontier of AI
  • Excellent fundamentals:
  • Are fluent in Python and JavaScript and comfortable building full-stack applications.
  • Experience with production-grade APIs, eventing, and data engineering (cloud-native, ideally GCP/BigQuery or similar).
  • Comfortable owning services end-to-end: architecture, implementation, testing, observability.

Nice To Haves

  • Prior work on LLM tools/agents, retrieval systems, or ML infra.
  • Experience operating within highly regulated environments leveraging patient and clinical trial data.

Responsibilities

  • AI agents / copilots for internal teams (BD, clinical, comp-bio, lab).
  • Robust data pipelines into a governed warehouse / knowledge graph.
  • MCP-style servers and tooling so agents can safely talk to internal systems.
  • Work across the full product lifecycle: prototype, iterate, ship, and maintain

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What This Job Offers

Job Type

Full-time

Career Level

Mid Level

Education Level

No Education Listed

Number of Employees

11-50 employees

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