Founding AI Engineer: Applied Systems & Prototypes

Parisi Labs; New York, Northern (NY, KY); Hybrid; USD 180,000 - 260,000; Full time

Job summary

Parisi Labs is seeking a senior founding engineer to advance applied AI systems across model code, data workflows, and early customer proofs. You will own end-to-end software from research ideas to implementable prototypes and tools.

This role is hands-on, not purely platform or management, and you will help set the technical bar for the first engineers while shipping reliable systems with the team. You will collaborate across time-series models, decision systems, and developer tooling to

Qualifications

• Experience building applied AI systems in startup or data/infra environments.
• Proficiency in Python, TypeScript, or Go for end-to-end software.
• Experience with model-serving and data workflows.
• Familiarity with APIs, gRPC, and Kubernetes.

Responsibilities

• Build applied AI systems around time-series models and decisioning.
• Turn research ideas into prototypes, benchmarks, internal tools, and customer-proof artifacts.
• Build reusable systems from recurring forecasting, covariate search, data prep, readout, and evaluation work.
• Work across model code, data contracts, workflows, and lightweight internal or pilot-facing surfaces.
• Improve developer experience, observability, reliability, and deployment speed where those unlock more research or pilot throughput.
• Help set the technical bar for the first engineering hires.

Skills

Python

TypeScript

Go

Tools

DuckDB

DuckLake

Kubernetes

gRPC

FastAPI

Temporal

GCP

Modal

Job description

Parisi Labs is seeking a senior founding engineer to advance applied AI systems across model code, data workflows, and early customer proofs. You will own end-to-end software from research ideas to implementable prototypes and tools.

This role is hands-on, not purely platform or management, and you will help set the technical bar for the first engineers while shipping reliable systems with the team. You will collaborate across time-series models, decision systems, and developer tooling to