Applied AI Engineer: Risk & Schedule AI for Large Projects

Foresight Works; New York (NY); On-site; USD 180,000 - 230,000; Full time

Benefits offered by this job

Health

Dental

Vision

401(k)

PTO

Job summary

Foresight Works in New York is seeking an Applied AI Engineer to build the core ML engine for the Foresight platform. You will architect, train and deploy models for risk predictions and AI recommendations used across large construction projects.

This hands-on role requires owning features from design to release, collaborating with full-stack engineers, product and customers, and ensuring scalability, accuracy and observability.

Qualifications

• 3+ years of building and shipping ML models in production with backend ownership.
• 1+ year shipping VLM/LLM features to production.
• Strong Python backend experience (FastAPI, Django or similar).
• Relational data modeling in PostgreSQL with ORM like SQLAlchemy.
• Experience with async queues, retries and idempotent work.
• Familiarity with AWS services (S3, RDS, queues or event services).

Responsibilities

• Own features from design through release and beyond, measuring adoption.
• Collaborate with full stack engineers to productionize new models.
• Partner with product, design and customers to identify high-impact problems.
• Tune performance across modeling stack for accuracy, latency and reliability.
• Raise the bar on architecture, testing, observability and shipping.
• Help shape the product and technical roadmap.

Skills

ML model ownership

LLM features

Python backend

PostgreSQL modeling

SQLAlchemy

Async/work queues

AWS

Tools

PostgreSQL

SQLAlchemy

Airflow

Temporal / Step Functions

Air/Video data pipelines

Job description

Foresight Works in New York is seeking an Applied AI Engineer to build the core ML engine for the Foresight platform. You will architect, train and deploy models for risk predictions and AI recommendations used across large construction projects.

This hands-on role requires owning features from design to release, collaborating with full-stack engineers, product and customers, and ensuring scalability, accuracy and observability.