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Inductive Bio · 1 day ago

AI Engineer

New York City, San Francisco, or Boston

Full-time

Onsite

Mid, Senior Level

$170K/yr - $230K/yr

4+ years exp

Inductive Bio is a company focused on transforming drug discovery through AI. They are seeking an AI Engineer to develop agentic AI workflows that enhance the drug discovery process by collaborating with medicinal chemists and improving system reliability and scalability.

BiotechnologyMedical

Responsibilities

Own the implementation of end-to-end agentic AI workflows, from data ingestion and schema design to prompting, context management, tool creation, and multi-agent orchestration

Partner closely with medicinal chemists to prototype, test, and refine AI-assisted workflows that improve scientific quality, speed, and confidence

Improve real user use cases by incorporating feedback from internal users (and external customers post-launch), translating insights into product and system improvements

Support automated integration of customer assay and experimental data into Indy environments, ensuring reliability and scalability

Identify and implement product improvements or new features based on hands-on collaboration with scientific, product, and engineering stakeholders

Contribute to backend and system architecture decisions as the platform evolves from single-user workflows to scalable, multi-user production systems

Qualification

PythonBackend systemsData engineeringLLMs integrationSchema designCollaborationProblem-solving

Required

4+ years of experience building backend and/or data systems using Python in production environments

Experience shipping at least one user-facing system that integrates LLMs (agentic workflows are a strong plus)

Strong understanding of backend systems, data flows, and production infrastructure

Comfort working with data engineering concepts such as schema design, pipelines, and orchestration (Dagster, Airflow, or similar tools)

Ability to collaborate deeply and effectively across disciplines, including working directly with scientists and translating domain-specific needs into robust technical solutions

Comfortable owning ambiguous problems, building from first principles, and iterating quickly in a startup environment