Founding Engineer, Applied AI

Parisi Labs•New York, NY

3d•Hybrid

About The Position

Parisi Labs is an AI research and product company building systems that understand how the physical world changes over time. We combine live data, forecasting, and interactive software so people can see what is happening, reason about what comes next, and make better decisions. Energy is our first proving ground. Ask The Grid is our live product for exploring the power system across markets, generation, demand, weather, and outages. It gives us a real environment in which to test models, ship useful tools, and learn from real users. We are a small team working across research, data, and product engineering. Everyone is expected to move from an ambiguous problem to a working system and to care whether the result is useful, reliable, and faithful to the underlying world. We are looking for an engineer who can turn new modeling and agent ideas into working systems. You will build evaluations, data and inference workflows, backend services, internal tools, and product-facing experiments while working directly with founders and researchers. Your job is to shorten the path from hypothesis to reliable software and bring failures observed in real products and real data back into the next experiment. This is not a narrow ML infrastructure role, a pure research role, or a management job.

Requirements

Senior hands-on engineer who wants to stay close to the code.
Ability to move between model-adjacent code, backend systems, data workflows, internal tools, and product surfaces without waiting for a perfect specification.
Strong technical judgment and ability to explain tradeoffs clearly.
Comfortable with research ambiguity and deep care about shipping reliable software.
Ability to distinguish reusable technical capability from one-off customer work.
Desire to help define both the architecture and engineering culture of an early technical company.
Strong experience with Python and at least one production-oriented language or product stack such as TypeScript or Go.
Experience with model-serving systems, data workflows, evaluation harnesses, or applied ML.
Familiarity with APIs, gRPC, FastAPI-style services, Temporal, Kubernetes, GCP, Modal, or comparable infrastructure.
Experience with analytical data systems, object storage, queues, or warehouse-backed tools.
A record of taking prototypes into reliable, repeatable, customer-credible operation.
High standards for testing, observability, security, reliability, and deployment without overbuilding.

Responsibilities

Turn research ideas into working prototypes, evaluations, internal tools, and customer-ready capabilities.
Build reusable systems for forecasting, covariate search, data preparation, evaluation, and decision support.
Work across model code, APIs, data contracts, workflows, backend services, and lightweight product surfaces.
Improve developer experience, observability, reliability, security, and deployment speed where they unlock more research and product throughput.
Collaborate directly with the CTO, Chief Scientist, and CEO on product and technical direction.
Help set the technical standard for the engineering team we are building.