Staff Software / AI Engineer

Pathos • New York, NY

2h • $180,000 - $200,000 • Hybrid

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 are designing a new stack from the ground up. We are hiring an engineer to architect and ship the first generation of Pathos AI and data infrastructure. Your work will power our core products and run the agents that support BD, clinical development, computational biology, and lab teams. This is an early role with broad technical scope and full 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. It is one of the most direct applications of your engineering skill to advances in cancer research.

Requirements

• Architected and owned a production system end to end, from design through observability, that real users depend on.
• Shipped LLM powered workflows in production, not just prototyped them.
• Know how technologies like LangGraph work and not just use it as a library.
• Make high judgment technical calls at the system level, not just execute well-scoped tasks.
• Move quickly, take initiative, and operate with a strong sense of ownership.
• 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.
• 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.
• Own services end to end: architecture, implementation, testing, and observability.

Nice To Haves

• 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.

Responsibilities

• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed