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, but as the operating system for how medicines get developed. We believe most drugs don’t fail because the science was wrong. They fail because they were tested in the wrong patients, with the wrong assumptions, in trials that couldn’t answer the real question: who benefits, and why?

Pathos exists to change that. We’re building the largest foundation model in oncology and pairing it with proprietary AI systems, deep oncology expertise, and 200+ petabytes of multimodal data linked to patient outcomes, so we can make development decisions with more precision, much earlier.

This is not theoretical. We’re well-capitalized and have the leadership to build a generational company. We invest in and advance our own clinical-stage programs, using our AI platform to sharpen trial design, patient selection and biomarker strategy. So therapies reach the patients most likely to benefit, sooner.

If you’re driven by purpose, energized by complexity, and want to apply AI, biology, or both to redefine the future drug development, come build Pathos with us.

About the role

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.

What You’ll Build

• 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

Who You Are

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

Location

This is a hybrid role, requiring up to 3-4 days per week onsite, in our NYC Headquarters.