Founding AI Engineer, Applied World Models

Parisi Labs, Inc.; New York (NY); On-site; USD 225,000 - 280,000; Full time

Benefits offered by this job

Equity

Job summary

Parisi Labs, Inc. is seeking a software engineer to turn new modeling and agent ideas into working systems in New York City or Boston.

You will build evaluations, data and inference workflows, backend services, internal tools, and product-facing experiments while collaborating directly with the founders and researchers. You will shorten the path from hypothesis to reliable software, turning model outputs into useful forecasting, scenario exploration, and decision-support capabilities.

Qualifications

• Track record turning ambiguous technical problems into production-ready software.
• Hands-on experience taking ML models or agent-based systems into production, including evaluation and maintenance.
• Ability to work in both research code and production-grade services with reliable tooling.
• Good technical judgment on reuse vs. new builds.

Responsibilities

• Turn research ideas into working prototypes, evaluations, and customer-ready capabilities.
• Build reusable systems for forecasting, data prep, inference, evaluation, and decision support.
• Work across model code, APIs, data contracts, and backend services.
• Investigate failures and improve evaluations and reliability.
• Improve developer experience, observability, security, and deployment speed.
• Collaborate with CTO, Chief Scientist, and CEO on technical direction and deployments.
• Set engineering standards, including testing and documentation.

Skills

Backend services

APIs

Data workflows

Testing & debugging

Job description

Parisi Labs, Inc. is seeking a software engineer to turn new modeling and agent ideas into working systems in New York City or Boston.

You will build evaluations, data and inference workflows, backend services, internal tools, and product-facing experiments while collaborating directly with the founders and researchers. You will shorten the path from hypothesis to reliable software, turning model outputs into useful forecasting, scenario exploration, and decision-support capabilities.