Full-Stack Engineer: Temporal AI Platform

Abel AI; Northern (KY); Hybrid; USD 110,000 - 160,000; Full time

Job summary

Abel AI in the United States is seeking a Full-Stack Engineer to build a platform for large-scale temporal foundation models. The role spans backend systems, data infrastructure, cloud services, and product engineering to enable ingestion, model inference, forecasting, and results delivery.

You will work with researchers to turn new temporal capability into robust production features, designing APIs and infrastructure for reliable end-to-end systems in a fast-moving environment.

Qualifications

• Build production-grade backend APIs and services.
• Design systems to handle large datasets with reliable performance.
• Collaborate across ML, data, and frontend teams to ship features.

Responsibilities

• Build the core temporal AI platform—from data ingestion to model inference and results delivery.
• Create backend systems connecting large temporal models with data pipelines, APIs, and apps.
• Develop scalable, low-latency inference services for forecasting and model workloads.
• Build data-intensive infrastructure for time-series, tabular, and structured data.
• Deploy, monitor, and operate production cloud workloads with reliability.
• Collaborate with ML researchers to translate capabilities into production features.
• Ship end-to-end systems across backend, data, ML infra, and deployment.

Skills

Backend API design

Distributed systems

Frontend development

Cloud services

ML system familiarity

Data handling (time-series)

Agile collaboration

Production-grade software

Tools

FastAPI

Flask

Django

Node.js

Docker

Kubernetes

Terraform

CI/CD

Observability tools

Job description

Abel AI in the United States is seeking a Full-Stack Engineer to build a platform for large-scale temporal foundation models. The role spans backend systems, data infrastructure, cloud services, and product engineering to enable ingestion, model inference, forecasting, and results delivery.

You will work with researchers to turn new temporal capability into robust production features, designing APIs and infrastructure for reliable end-to-end systems in a fast-moving environment.